Overview

Dataset statistics

Number of variables35
Number of observations9999
Missing cells13520
Missing cells (%)3.9%
Duplicate rows46
Duplicate rows (%)0.5%
Total size in memory2.6 MiB
Average record size in memory273.0 B

Variable types

Text15
Numeric14
Boolean1
Categorical3
DateTime1
Unsupported1

Alerts

Added By has constant value "spotify:user:bradnumber1"Constant
Dataset has 46 (0.5%) duplicate rowsDuplicates
Acousticness is highly overall correlated with EnergyHigh correlation
Danceability is highly overall correlated with Time SignatureHigh correlation
Energy is highly overall correlated with Acousticness and 1 other fieldsHigh correlation
Loudness is highly overall correlated with EnergyHigh correlation
Tempo is highly overall correlated with Time SignatureHigh correlation
Time Signature is highly overall correlated with Danceability and 1 other fieldsHigh correlation
Explicit is highly imbalanced (71.0%)Imbalance
Time Signature is highly imbalanced (86.6%)Imbalance
Track Preview URL has 2897 (29.0%) missing valuesMissing
Artist Genres has 550 (5.5%) missing valuesMissing
Album Genres has 9999 (100.0%) missing valuesMissing
Disc Number is highly skewed (γ1 = 22.25399104)Skewed
Album Genres is an unsupported type, check if it needs cleaning or further analysisUnsupported
Popularity has 2669 (26.7%) zerosZeros
Key has 1315 (13.2%) zerosZeros
Instrumentalness has 3996 (40.0%) zerosZeros

Reproduction

Analysis started2024-06-13 11:14:13.892809
Analysis finished2024-06-13 11:15:15.132789
Duration1 minute and 1.24 second
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Distinct9951
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:15.463496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length75
Median length36
Mean length36.007701
Min length36

Characters and Unicode

Total characters360041
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9905 ?
Unique (%)99.1%

Sample

1st rowspotify:track:1XAZlnVtthcDZt2NI1Dtxo
2nd rowspotify:track:6a8GbQIlV8HBUW3c6Uk9PH
3rd rowspotify:track:70XtWbcVZcpaOddJftMcVi
4th rowspotify:track:1NXUWyPJk5kO6DQJ5t7bDu
5th rowspotify:track:72WZtWs6V7uu3aMgMmEkYe
ValueCountFrequency (%)
spotify:track:7hqja50xrcwabau5v6qz4i 3
 
< 0.1%
spotify:track:4alho6rgd0d3oubtpexthn 3
 
< 0.1%
spotify:track:2sxp9qmvc7mradbjbgcggi 2
 
< 0.1%
spotify:track:7tfiytwd0nx5a1eklytx2j 2
 
< 0.1%
spotify:track:1nrbnhlr2bfrecywxhihip 2
 
< 0.1%
spotify:track:3llaycyu26dvfzbduimb7a 2
 
< 0.1%
spotify:track:2xpc8gl9pwxgurqfcfadjr 2
 
< 0.1%
spotify:track:75wp08atmfgfjk0npdvvw3 2
 
< 0.1%
spotify:track:1mtmedlcphum6mrcd8yzve 2
 
< 0.1%
spotify:track:0iyeaciamtiv8xmkbg97fy 2
 
< 0.1%
Other values (9941) 9977
99.8%
2024-06-13T11:15:16.160408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 23429
 
6.5%
: 20004
 
5.6%
c 13455
 
3.7%
i 13432
 
3.7%
o 13400
 
3.7%
f 13399
 
3.7%
p 13384
 
3.7%
s 13383
 
3.7%
r 13374
 
3.7%
y 13347
 
3.7%
Other values (56) 209434
58.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 360041
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 23429
 
6.5%
: 20004
 
5.6%
c 13455
 
3.7%
i 13432
 
3.7%
o 13400
 
3.7%
f 13399
 
3.7%
p 13384
 
3.7%
s 13383
 
3.7%
r 13374
 
3.7%
y 13347
 
3.7%
Other values (56) 209434
58.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 360041
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 23429
 
6.5%
: 20004
 
5.6%
c 13455
 
3.7%
i 13432
 
3.7%
o 13400
 
3.7%
f 13399
 
3.7%
p 13384
 
3.7%
s 13383
 
3.7%
r 13374
 
3.7%
y 13347
 
3.7%
Other values (56) 209434
58.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 360041
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 23429
 
6.5%
: 20004
 
5.6%
c 13455
 
3.7%
i 13432
 
3.7%
o 13400
 
3.7%
f 13399
 
3.7%
p 13384
 
3.7%
s 13383
 
3.7%
r 13374
 
3.7%
y 13347
 
3.7%
Other values (56) 209434
58.2%
Distinct8258
Distinct (%)82.6%
Missing1
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:16.635547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length150
Median length84
Mean length18.810662
Min length1

Characters and Unicode

Total characters188069
Distinct characters103
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6961 ?
Unique (%)69.6%

Sample

1st rowJustified & Ancient - Stand by the Jams
2nd rowI Know You Want Me (Calle Ocho)
3rd rowFrom the Bottom of My Broken Heart
4th rowApeman - 2014 Remastered Version
5th rowYou Can't Always Get What You Want
ValueCountFrequency (%)
1610
 
4.4%
the 1266
 
3.4%
you 988
 
2.7%
i 676
 
1.8%
me 637
 
1.7%
love 633
 
1.7%
feat 540
 
1.5%
a 441
 
1.2%
to 423
 
1.1%
of 419
 
1.1%
Other values (5288) 29293
79.3%
2024-06-13T11:15:17.441157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26928
 
14.3%
e 18075
 
9.6%
o 11825
 
6.3%
a 10087
 
5.4%
t 8952
 
4.8%
n 8915
 
4.7%
i 8745
 
4.6%
r 7837
 
4.2%
s 5718
 
3.0%
l 5459
 
2.9%
Other values (93) 75528
40.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 188069
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
26928
 
14.3%
e 18075
 
9.6%
o 11825
 
6.3%
a 10087
 
5.4%
t 8952
 
4.8%
n 8915
 
4.7%
i 8745
 
4.6%
r 7837
 
4.2%
s 5718
 
3.0%
l 5459
 
2.9%
Other values (93) 75528
40.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 188069
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
26928
 
14.3%
e 18075
 
9.6%
o 11825
 
6.3%
a 10087
 
5.4%
t 8952
 
4.8%
n 8915
 
4.7%
i 8745
 
4.6%
r 7837
 
4.2%
s 5718
 
3.0%
l 5459
 
2.9%
Other values (93) 75528
40.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 188069
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
26928
 
14.3%
e 18075
 
9.6%
o 11825
 
6.3%
a 10087
 
5.4%
t 8952
 
4.8%
n 8915
 
4.7%
i 8745
 
4.6%
r 7837
 
4.2%
s 5718
 
3.0%
l 5459
 
2.9%
Other values (93) 75528
40.2%
Distinct4134
Distinct (%)41.4%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:17.873991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length271
Median length37
Mean length44.860858
Min length37

Characters and Unicode

Total characters448474
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2538 ?
Unique (%)25.4%

Sample

1st rowspotify:artist:6dYrdRlNZSKaVxYg5IrvCH
2nd rowspotify:artist:0TnOYISbd1XYRBk9myaseg
3rd rowspotify:artist:26dSoYclwsYLMAKD3tpOr4
4th rowspotify:artist:1SQRv42e4PjEYfPhS0Tk9E
5th rowspotify:artist:22bE4uQ6baNwSHPVcDxLCe
ValueCountFrequency (%)
spotify:artist:6eukzxakkcvih0ku9w2n3v 64
 
0.5%
spotify:artist:1unfozahbgtllmzznpci3s 63
 
0.5%
spotify:artist:06hl4z0cvfaxyc27gxpf02 59
 
0.5%
spotify:artist:1kcspy1glikqw2totwuxor 56
 
0.5%
spotify:artist:5pkccke2ajjhz9kaiak11h 51
 
0.4%
spotify:artist:43zhct0cazbisjo8dg9pne 47
 
0.4%
spotify:artist:1cs0zkbu1kc0i8ypk3b9ai 47
 
0.4%
spotify:artist:04gdigrs5kc9ywfzhwbetp 44
 
0.4%
spotify:artist:6tbjwdeizxodsba1fuhfpw 42
 
0.3%
spotify:artist:51blml2lzpmy7ttiag47vq 42
 
0.3%
Other values (3772) 11497
95.7%
2024-06-13T11:15:18.540491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 40257
 
9.0%
s 28033
 
6.3%
i 27894
 
6.2%
: 24024
 
5.4%
a 16466
 
3.7%
o 16411
 
3.7%
r 16358
 
3.6%
f 16083
 
3.6%
y 15917
 
3.5%
p 15863
 
3.5%
Other values (55) 231168
51.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 448474
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 40257
 
9.0%
s 28033
 
6.3%
i 27894
 
6.2%
: 24024
 
5.4%
a 16466
 
3.7%
o 16411
 
3.7%
r 16358
 
3.6%
f 16083
 
3.6%
y 15917
 
3.5%
p 15863
 
3.5%
Other values (55) 231168
51.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 448474
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 40257
 
9.0%
s 28033
 
6.3%
i 27894
 
6.2%
: 24024
 
5.4%
a 16466
 
3.7%
o 16411
 
3.7%
r 16358
 
3.6%
f 16083
 
3.6%
y 15917
 
3.5%
p 15863
 
3.5%
Other values (55) 231168
51.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 448474
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 40257
 
9.0%
s 28033
 
6.3%
i 27894
 
6.2%
: 24024
 
5.4%
a 16466
 
3.7%
o 16411
 
3.7%
r 16358
 
3.6%
f 16083
 
3.6%
y 15917
 
3.5%
p 15863
 
3.5%
Other values (55) 231168
51.5%
Distinct4129
Distinct (%)41.3%
Missing1
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:19.070744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length113
Median length64
Mean length13.718744
Min length2

Characters and Unicode

Total characters137160
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2531 ?
Unique (%)25.3%

Sample

1st rowThe KLF
2nd rowPitbull
3rd rowBritney Spears
4th rowThe Kinks
5th rowThe Rolling Stones
ValueCountFrequency (%)
the 1244
 
5.4%
324
 
1.4%
john 176
 
0.8%
david 95
 
0.4%
justin 93
 
0.4%
of 91
 
0.4%
james 80
 
0.3%
michael 79
 
0.3%
taylor 72
 
0.3%
and 71
 
0.3%
Other values (4510) 20807
89.9%
2024-06-13T11:15:20.052471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13136
 
9.6%
e 12898
 
9.4%
a 10251
 
7.5%
n 8086
 
5.9%
i 8058
 
5.9%
r 7165
 
5.2%
o 7147
 
5.2%
l 6095
 
4.4%
s 5544
 
4.0%
t 4659
 
3.4%
Other values (89) 54121
39.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 137160
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
13136
 
9.6%
e 12898
 
9.4%
a 10251
 
7.5%
n 8086
 
5.9%
i 8058
 
5.9%
r 7165
 
5.2%
o 7147
 
5.2%
l 6095
 
4.4%
s 5544
 
4.0%
t 4659
 
3.4%
Other values (89) 54121
39.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 137160
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
13136
 
9.6%
e 12898
 
9.4%
a 10251
 
7.5%
n 8086
 
5.9%
i 8058
 
5.9%
r 7165
 
5.2%
o 7147
 
5.2%
l 6095
 
4.4%
s 5544
 
4.0%
t 4659
 
3.4%
Other values (89) 54121
39.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 137160
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
13136
 
9.6%
e 12898
 
9.4%
a 10251
 
7.5%
n 8086
 
5.9%
i 8058
 
5.9%
r 7165
 
5.2%
o 7147
 
5.2%
l 6095
 
4.4%
s 5544
 
4.0%
t 4659
 
3.4%
Other values (89) 54121
39.5%
Distinct7462
Distinct (%)74.6%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:20.721502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters359892
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5920 ?
Unique (%)59.2%

Sample

1st rowspotify:album:4MC0ZjNtVP1nDD5lsLxFjc
2nd rowspotify:album:5xLAcbvbSAlRtPXnKkggXA
3rd rowspotify:album:3WNxdumkSMGMJRhEgK80qx
4th rowspotify:album:6lL6HugNEN4Vlc8sj0Zcse
5th rowspotify:album:0c78nsgqX6VfniSNWIxwoD
ValueCountFrequency (%)
spotify:album:43lok9zd7bw5coykxzs7s0 15
 
0.2%
spotify:album:7fzh0auajy3ay25obouf2a 11
 
0.1%
spotify:album:4eki4pjuybybksbe6nnqnd 11
 
0.1%
spotify:album:1zcnrbppz5olsr6msppdkm 10
 
0.1%
spotify:album:7k7ahow1mgwwqr0kxvswkx 9
 
0.1%
spotify:album:2oxzjlxxm8jry3gbovnfmz 9
 
0.1%
spotify:album:5jsakaic1bbkzqsz7wfyoy 9
 
0.1%
spotify:album:1xn54dmo2qiqbumqhtusfd 9
 
0.1%
spotify:album:3t4tuhgyernvugevb0wthu 8
 
0.1%
spotify:album:7uwthxmfa1ebi5flqbosig 8
 
0.1%
Other values (7452) 9898
99.0%
2024-06-13T11:15:21.804386image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 19994
 
5.6%
o 13581
 
3.8%
i 13511
 
3.8%
l 13495
 
3.7%
m 13494
 
3.7%
b 13466
 
3.7%
t 13453
 
3.7%
f 13419
 
3.7%
u 13413
 
3.7%
p 13390
 
3.7%
Other values (53) 218676
60.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 359892
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
: 19994
 
5.6%
o 13581
 
3.8%
i 13511
 
3.8%
l 13495
 
3.7%
m 13494
 
3.7%
b 13466
 
3.7%
t 13453
 
3.7%
f 13419
 
3.7%
u 13413
 
3.7%
p 13390
 
3.7%
Other values (53) 218676
60.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 359892
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
: 19994
 
5.6%
o 13581
 
3.8%
i 13511
 
3.8%
l 13495
 
3.7%
m 13494
 
3.7%
b 13466
 
3.7%
t 13453
 
3.7%
f 13419
 
3.7%
u 13413
 
3.7%
p 13390
 
3.7%
Other values (53) 218676
60.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 359892
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
: 19994
 
5.6%
o 13581
 
3.8%
i 13511
 
3.8%
l 13495
 
3.7%
m 13494
 
3.7%
b 13466
 
3.7%
t 13453
 
3.7%
f 13419
 
3.7%
u 13413
 
3.7%
p 13390
 
3.7%
Other values (53) 218676
60.8%
Distinct6636
Distinct (%)66.4%
Missing1
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:22.930142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length153
Median length89
Mean length20.058212
Min length1

Characters and Unicode

Total characters200542
Distinct characters113
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4906 ?
Unique (%)49.1%

Sample

1st rowSongs Collection
2nd rowPitbull Starring In Rebelution
3rd row...Baby One More Time (Digital Deluxe Version)
4th rowLola vs. Powerman and the Moneygoround, Pt. One + Percy (Super Deluxe)
5th rowLet It Bleed
ValueCountFrequency (%)
the 2526
 
7.2%
of 984
 
2.8%
801
 
2.3%
deluxe 648
 
1.9%
best 565
 
1.6%
edition 525
 
1.5%
hits 470
 
1.3%
greatest 329
 
0.9%
version 329
 
0.9%
you 319
 
0.9%
Other values (5754) 27346
78.5%
2024-06-13T11:15:24.419365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24844
 
12.4%
e 20252
 
10.1%
o 11099
 
5.5%
i 10570
 
5.3%
t 10477
 
5.2%
n 9892
 
4.9%
a 9679
 
4.8%
r 8737
 
4.4%
s 8460
 
4.2%
l 7109
 
3.5%
Other values (103) 79423
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 200542
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
24844
 
12.4%
e 20252
 
10.1%
o 11099
 
5.5%
i 10570
 
5.3%
t 10477
 
5.2%
n 9892
 
4.9%
a 9679
 
4.8%
r 8737
 
4.4%
s 8460
 
4.2%
l 7109
 
3.5%
Other values (103) 79423
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 200542
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
24844
 
12.4%
e 20252
 
10.1%
o 11099
 
5.5%
i 10570
 
5.3%
t 10477
 
5.2%
n 9892
 
4.9%
a 9679
 
4.8%
r 8737
 
4.4%
s 8460
 
4.2%
l 7109
 
3.5%
Other values (103) 79423
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 200542
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
24844
 
12.4%
e 20252
 
10.1%
o 11099
 
5.5%
i 10570
 
5.3%
t 10477
 
5.2%
n 9892
 
4.9%
a 9679
 
4.8%
r 8737
 
4.4%
s 8460
 
4.2%
l 7109
 
3.5%
Other values (103) 79423
39.6%
Distinct3298
Distinct (%)33.0%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:24.922808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length271
Median length37
Mean length39.360208
Min length37

Characters and Unicode

Total characters393484
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1839 ?
Unique (%)18.4%

Sample

1st rowspotify:artist:6dYrdRlNZSKaVxYg5IrvCH
2nd rowspotify:artist:0TnOYISbd1XYRBk9myaseg
3rd rowspotify:artist:26dSoYclwsYLMAKD3tpOr4
4th rowspotify:artist:1SQRv42e4PjEYfPhS0Tk9E
5th rowspotify:artist:22bE4uQ6baNwSHPVcDxLCe
ValueCountFrequency (%)
spotify:artist:0lyfqwjt6nxaflpzqxe9of 393
 
3.7%
spotify:artist:06hl4z0cvfaxyc27gxpf02 53
 
0.5%
spotify:artist:1kcspy1glikqw2totwuxor 52
 
0.5%
spotify:artist:6eukzxakkcvih0ku9w2n3v 52
 
0.5%
spotify:artist:1unfozahbgtllmzznpci3s 49
 
0.5%
spotify:artist:43zhct0cazbisjo8dg9pne 47
 
0.4%
spotify:artist:1cs0zkbu1kc0i8ypk3b9ai 42
 
0.4%
spotify:artist:51blml2lzpmy7ttiag47vq 42
 
0.4%
spotify:artist:04gdigrs5kc9ywfzhwbetp 42
 
0.4%
spotify:artist:6tbjwdeizxodsba1fuhfpw 40
 
0.4%
Other values (3185) 9790
92.3%
2024-06-13T11:15:25.638287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 35428
 
9.0%
s 24614
 
6.3%
i 24466
 
6.2%
: 21204
 
5.4%
f 15312
 
3.9%
a 14769
 
3.8%
o 14345
 
3.6%
r 14269
 
3.6%
y 14210
 
3.6%
p 13861
 
3.5%
Other values (55) 201006
51.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 393484
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 35428
 
9.0%
s 24614
 
6.3%
i 24466
 
6.2%
: 21204
 
5.4%
f 15312
 
3.9%
a 14769
 
3.8%
o 14345
 
3.6%
r 14269
 
3.6%
y 14210
 
3.6%
p 13861
 
3.5%
Other values (55) 201006
51.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 393484
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 35428
 
9.0%
s 24614
 
6.3%
i 24466
 
6.2%
: 21204
 
5.4%
f 15312
 
3.9%
a 14769
 
3.8%
o 14345
 
3.6%
r 14269
 
3.6%
y 14210
 
3.6%
p 13861
 
3.5%
Other values (55) 201006
51.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 393484
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 35428
 
9.0%
s 24614
 
6.3%
i 24466
 
6.2%
: 21204
 
5.4%
f 15312
 
3.9%
a 14769
 
3.8%
o 14345
 
3.6%
r 14269
 
3.6%
y 14210
 
3.6%
p 13861
 
3.5%
Other values (55) 201006
51.1%
Distinct3294
Distinct (%)32.9%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:26.140736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length80
Median length48
Mean length12.13374
Min length2

Characters and Unicode

Total characters121301
Distinct characters97
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1833 ?
Unique (%)18.3%

Sample

1st rowThe KLF
2nd rowPitbull
3rd rowBritney Spears
4th rowThe Kinks
5th rowThe Rolling Stones
ValueCountFrequency (%)
the 1157
 
5.6%
artists 394
 
1.9%
various 393
 
1.9%
299
 
1.5%
john 142
 
0.7%
david 87
 
0.4%
of 86
 
0.4%
michael 77
 
0.4%
james 71
 
0.3%
justin 67
 
0.3%
Other values (3949) 17827
86.5%
2024-06-13T11:15:26.992925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11155
 
9.2%
10605
 
8.7%
a 9073
 
7.5%
i 7566
 
6.2%
r 7009
 
5.8%
n 6872
 
5.7%
o 6591
 
5.4%
s 6028
 
5.0%
l 5195
 
4.3%
t 4841
 
4.0%
Other values (87) 46366
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 121301
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11155
 
9.2%
10605
 
8.7%
a 9073
 
7.5%
i 7566
 
6.2%
r 7009
 
5.8%
n 6872
 
5.7%
o 6591
 
5.4%
s 6028
 
5.0%
l 5195
 
4.3%
t 4841
 
4.0%
Other values (87) 46366
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 121301
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11155
 
9.2%
10605
 
8.7%
a 9073
 
7.5%
i 7566
 
6.2%
r 7009
 
5.8%
n 6872
 
5.7%
o 6591
 
5.4%
s 6028
 
5.0%
l 5195
 
4.3%
t 4841
 
4.0%
Other values (87) 46366
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 121301
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11155
 
9.2%
10605
 
8.7%
a 9073
 
7.5%
i 7566
 
6.2%
r 7009
 
5.8%
n 6872
 
5.7%
o 6591
 
5.4%
s 6028
 
5.0%
l 5195
 
4.3%
t 4841
 
4.0%
Other values (87) 46366
38.2%
Distinct3332
Distinct (%)33.3%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:27.504783image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.1873562
Min length4

Characters and Unicode

Total characters91846
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1791 ?
Unique (%)17.9%

Sample

1st row1992-08-03
2nd row2009-10-23
3rd row1999-01-12
4th row2014-10-20
5th row1969-12-05
ValueCountFrequency (%)
2009-01-01 130
 
1.3%
2011-01-01 128
 
1.3%
2013-01-01 107
 
1.1%
2010-01-01 98
 
1.0%
2008-01-01 82
 
0.8%
2012-01-01 81
 
0.8%
2005-01-01 81
 
0.8%
2014-01-01 76
 
0.8%
2007-01-01 75
 
0.8%
2006-01-01 73
 
0.7%
Other values (3322) 9066
90.7%
2024-06-13T11:15:28.276019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22278
24.3%
1 18210
19.8%
- 17286
18.8%
2 11560
12.6%
9 7052
 
7.7%
8 3067
 
3.3%
7 2967
 
3.2%
6 2633
 
2.9%
3 2490
 
2.7%
5 2245
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 91846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22278
24.3%
1 18210
19.8%
- 17286
18.8%
2 11560
12.6%
9 7052
 
7.7%
8 3067
 
3.3%
7 2967
 
3.2%
6 2633
 
2.9%
3 2490
 
2.7%
5 2245
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 91846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22278
24.3%
1 18210
19.8%
- 17286
18.8%
2 11560
12.6%
9 7052
 
7.7%
8 3067
 
3.3%
7 2967
 
3.2%
6 2633
 
2.9%
3 2490
 
2.7%
5 2245
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 91846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22278
24.3%
1 18210
19.8%
- 17286
18.8%
2 11560
12.6%
9 7052
 
7.7%
8 3067
 
3.3%
7 2967
 
3.2%
6 2633
 
2.9%
3 2490
 
2.7%
5 2245
 
2.4%
Distinct7460
Distinct (%)74.6%
Missing4
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:28.793281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters639680
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5918 ?
Unique (%)59.2%

Sample

1st rowhttps://i.scdn.co/image/ab67616d0000b27355346bc1f268730f607f9544
2nd rowhttps://i.scdn.co/image/ab67616d0000b27326d73ab8423a350faa5d395a
3rd rowhttps://i.scdn.co/image/ab67616d0000b2738e49866860c25afffe2f1a02
4th rowhttps://i.scdn.co/image/ab67616d0000b2731e7c5307ccbbb74101e0cc77
5th rowhttps://i.scdn.co/image/ab67616d0000b27373d92707b0e7da0c493f5b86
ValueCountFrequency (%)
https://i.scdn.co/image/ab67616d0000b2731fc9fd5d701ee05cb39b7b19 15
 
0.2%
https://i.scdn.co/image/ab67616d0000b273b6d9a4fbb0bd49f0f034aead 11
 
0.1%
https://i.scdn.co/image/ab67616d0000b273d029ad5d1a40fabfae0ac7f3 11
 
0.1%
https://i.scdn.co/image/ab67616d0000b273136d7250568820409f8fdd60 10
 
0.1%
https://i.scdn.co/image/ab67616d0000b273a589a051c46a5ff41125e9d6 9
 
0.1%
https://i.scdn.co/image/ab67616d0000b273576629f3c4631eb55612a7c7 9
 
0.1%
https://i.scdn.co/image/ab67616d0000b27310df926bec224d743644ea3e 9
 
0.1%
https://i.scdn.co/image/ab67616d0000b27313b3e37318a0c247b550bccd 9
 
0.1%
https://i.scdn.co/image/ab67616d0000b273ba5db46f4b838ef6027e6f96 8
 
0.1%
https://i.scdn.co/image/ab67616d0000b2735ffbbc3dca25d5c81491af1f 8
 
0.1%
Other values (7450) 9896
99.0%
2024-06-13T11:15:29.506214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54813
 
8.6%
6 44953
 
7.0%
/ 39980
 
6.2%
a 35340
 
5.5%
d 35201
 
5.5%
b 35020
 
5.5%
c 34889
 
5.5%
7 34819
 
5.4%
1 25181
 
3.9%
e 25140
 
3.9%
Other values (18) 274344
42.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 639680
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 54813
 
8.6%
6 44953
 
7.0%
/ 39980
 
6.2%
a 35340
 
5.5%
d 35201
 
5.5%
b 35020
 
5.5%
c 34889
 
5.5%
7 34819
 
5.4%
1 25181
 
3.9%
e 25140
 
3.9%
Other values (18) 274344
42.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 639680
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 54813
 
8.6%
6 44953
 
7.0%
/ 39980
 
6.2%
a 35340
 
5.5%
d 35201
 
5.5%
b 35020
 
5.5%
c 34889
 
5.5%
7 34819
 
5.4%
1 25181
 
3.9%
e 25140
 
3.9%
Other values (18) 274344
42.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 639680
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 54813
 
8.6%
6 44953
 
7.0%
/ 39980
 
6.2%
a 35340
 
5.5%
d 35201
 
5.5%
b 35020
 
5.5%
c 34889
 
5.5%
7 34819
 
5.4%
1 25181
 
3.9%
e 25140
 
3.9%
Other values (18) 274344
42.9%

Disc Number
Real number (ℝ)

SKEWED 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0351035
Minimum0
Maximum15
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:29.813407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.32785571
Coefficient of variation (CV)0.31673712
Kurtosis765.88964
Mean1.0351035
Median Absolute Deviation (MAD)0
Skewness22.253991
Sum10350
Variance0.10748936
MonotonicityNot monotonic
2024-06-13T11:15:30.024672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 9766
97.7%
2 178
 
1.8%
3 28
 
0.3%
4 11
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
15 2
 
< 0.1%
0 2
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 9766
97.7%
2 178
 
1.8%
3 28
 
0.3%
4 11
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
15 2
 
< 0.1%
ValueCountFrequency (%)
15 2
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
6 3
 
< 0.1%
5 7
 
0.1%
4 11
 
0.1%
3 28
 
0.3%
2 178
 
1.8%
1 9766
97.7%
0 2
 
< 0.1%

Track Number
Real number (ℝ)

Distinct57
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9570957
Minimum0
Maximum93
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:30.287528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median3
Q37
95-th percentile15
Maximum93
Range93
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.5028098
Coefficient of variation (CV)1.1100875
Kurtosis33.462129
Mean4.9570957
Median Absolute Deviation (MAD)2
Skewness3.8054907
Sum49566
Variance30.280916
MonotonicityNot monotonic
2024-06-13T11:15:30.578901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3232
32.3%
2 1222
 
12.2%
3 968
 
9.7%
4 755
 
7.6%
5 594
 
5.9%
6 566
 
5.7%
7 432
 
4.3%
8 335
 
3.4%
10 316
 
3.2%
9 311
 
3.1%
Other values (47) 1268
 
12.7%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 3232
32.3%
2 1222
 
12.2%
3 968
 
9.7%
4 755
 
7.6%
5 594
 
5.9%
6 566
 
5.7%
7 432
 
4.3%
8 335
 
3.4%
9 311
 
3.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
92 1
 
< 0.1%
84 1
 
< 0.1%
83 1
 
< 0.1%
75 1
 
< 0.1%
61 1
 
< 0.1%
60 1
 
< 0.1%
57 1
 
< 0.1%
53 3
< 0.1%
51 1
 
< 0.1%

Track Duration (ms)
Real number (ℝ)

Distinct7320
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224814.97
Minimum0
Maximum1561133
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:31.368882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile150133
Q1192579.5
median219906
Q3250260
95-th percentile312737
Maximum1561133
Range1561133
Interquartile range (IQR)57680.5

Descriptive statistics

Standard deviation54100.116
Coefficient of variation (CV)0.24064285
Kurtosis46.906075
Mean224814.97
Median Absolute Deviation (MAD)28734
Skewness2.9873575
Sum2.2479249 × 109
Variance2.9268226 × 109
MonotonicityNot monotonic
2024-06-13T11:15:31.665367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208106 8
 
0.1%
227266 8
 
0.1%
240800 7
 
0.1%
235266 7
 
0.1%
228000 6
 
0.1%
171826 6
 
0.1%
208733 6
 
0.1%
226986 6
 
0.1%
224133 6
 
0.1%
231333 6
 
0.1%
Other values (7310) 9933
99.3%
ValueCountFrequency (%)
0 1
< 0.1%
91226 1
< 0.1%
94333 1
< 0.1%
97506 1
< 0.1%
97946 1
< 0.1%
103026 1
< 0.1%
103560 1
< 0.1%
105200 1
< 0.1%
106066 1
< 0.1%
106293 1
< 0.1%
ValueCountFrequency (%)
1561133 1
< 0.1%
1008533 1
< 0.1%
891720 1
< 0.1%
659000 1
< 0.1%
604266 1
< 0.1%
594453 1
< 0.1%
557293 1
< 0.1%
549000 1
< 0.1%
543560 1
< 0.1%
537506 1
< 0.1%

Track Preview URL
Text

MISSING 

Distinct6889
Distinct (%)97.0%
Missing2897
Missing (%)29.0%
Memory size78.2 KiB
2024-06-13T11:15:32.146958image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length107
Median length107
Mean length107
Min length107

Characters and Unicode

Total characters759914
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6691 ?
Unique (%)94.2%

Sample

1st rowhttps://p.scdn.co/mp3-preview/d6f8883fc955cb0ecb7f3e1e06e77a9d8611158d?cid=9950ac751e34487dbbe027c4fd7f8e99
2nd rowhttps://p.scdn.co/mp3-preview/1de5faef947224dcb7efb26a5303ae0735b28167?cid=9950ac751e34487dbbe027c4fd7f8e99
3rd rowhttps://p.scdn.co/mp3-preview/c4df3a832509cc5506bd0c91419146f78d864825?cid=9950ac751e34487dbbe027c4fd7f8e99
4th rowhttps://p.scdn.co/mp3-preview/64b1e9388ec19f29fa36d38d1f80f56d77df56a3?cid=9950ac751e34487dbbe027c4fd7f8e99
5th rowhttps://p.scdn.co/mp3-preview/24726be4c89b67eab298a72560b637581450421c?cid=9950ac751e34487dbbe027c4fd7f8e99
ValueCountFrequency (%)
https://p.scdn.co/mp3-preview/358cc2906abb9789b9c1d4a7e07dc2601b7ade4b?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/cafb65956f11cc3e26ee45642bddc1ed69146dd8?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/7581d37ad411cfa1c671605798429c2adc0c3052?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/107e8dfabb7be6126043e6ad26b86badd819675d?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/d56de4777551c3eb7430ecf289809b1653147bf8?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/394733516cbfb50de32d089428542875e77251ed?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/8721423c664c8ec64df22cd2a85711437431a98c?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/f5e385c67500e80a2c75311495dc6aa134f2958b?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/edb9b92942f6c44cea060e481d2f6fecff19fbb9?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
https://p.scdn.co/mp3-preview/dffa47dbbfe06cff32e8b676e66e7d50ad358ca7?cid=9950ac751e34487dbbe027c4fd7f8e99 3
 
< 0.1%
Other values (6879) 7072
99.6%
2024-06-13T11:15:32.830207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 53158
 
7.0%
c 53148
 
7.0%
7 46278
 
6.1%
9 46267
 
6.1%
d 46217
 
6.1%
4 39167
 
5.2%
5 32140
 
4.2%
b 32035
 
4.2%
0 31972
 
4.2%
f 31853
 
4.2%
Other values (23) 347679
45.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 759914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 53158
 
7.0%
c 53148
 
7.0%
7 46278
 
6.1%
9 46267
 
6.1%
d 46217
 
6.1%
4 39167
 
5.2%
5 32140
 
4.2%
b 32035
 
4.2%
0 31972
 
4.2%
f 31853
 
4.2%
Other values (23) 347679
45.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 759914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 53158
 
7.0%
c 53148
 
7.0%
7 46278
 
6.1%
9 46267
 
6.1%
d 46217
 
6.1%
4 39167
 
5.2%
5 32140
 
4.2%
b 32035
 
4.2%
0 31972
 
4.2%
f 31853
 
4.2%
Other values (23) 347679
45.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 759914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 53158
 
7.0%
c 53148
 
7.0%
7 46278
 
6.1%
9 46267
 
6.1%
d 46217
 
6.1%
4 39167
 
5.2%
5 32140
 
4.2%
b 32035
 
4.2%
0 31972
 
4.2%
f 31853
 
4.2%
Other values (23) 347679
45.8%

Explicit
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9490 
True
 
509
ValueCountFrequency (%)
False 9490
94.9%
True 509
 
5.1%
2024-06-13T11:15:33.105881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Popularity
Real number (ℝ)

ZEROS 

Distinct99
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.624662
Minimum0
Maximum98
Zeros2669
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:33.329676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median42
Q364
95-th percentile80
Maximum98
Range98
Interquartile range (IQR)64

Descriptive statistics

Standard deviation29.460808
Coefficient of variation (CV)0.78301854
Kurtosis-1.4458911
Mean37.624662
Median Absolute Deviation (MAD)27
Skewness-0.056447529
Sum376209
Variance867.93922
MonotonicityNot monotonic
2024-06-13T11:15:33.740409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2669
26.7%
69 154
 
1.5%
67 143
 
1.4%
54 141
 
1.4%
64 138
 
1.4%
65 132
 
1.3%
59 132
 
1.3%
62 131
 
1.3%
51 128
 
1.3%
60 128
 
1.3%
Other values (89) 6103
61.0%
ValueCountFrequency (%)
0 2669
26.7%
1 86
 
0.9%
2 58
 
0.6%
3 55
 
0.6%
4 32
 
0.3%
5 33
 
0.3%
6 24
 
0.2%
7 41
 
0.4%
8 29
 
0.3%
9 23
 
0.2%
ValueCountFrequency (%)
98 1
 
< 0.1%
97 1
 
< 0.1%
96 1
 
< 0.1%
95 5
 
0.1%
94 3
 
< 0.1%
93 4
 
< 0.1%
92 6
 
0.1%
91 10
0.1%
90 10
0.1%
89 15
0.2%

ISRC
Text

Distinct8948
Distinct (%)89.5%
Missing3
Missing (%)< 0.1%
Memory size78.2 KiB
2024-06-13T11:15:34.671805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.0009
Min length12

Characters and Unicode

Total characters119961
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8071 ?
Unique (%)80.7%

Sample

1st rowQMARG1760056
2nd rowUSJAY0900144
3rd rowUSJI19910455
4th rowGB5KW1499822
5th rowUSA176910100
ValueCountFrequency (%)
nlf057890004 6
 
0.1%
gbum70709792 5
 
0.1%
usir20300704 5
 
0.1%
gbum71308833 5
 
0.1%
usum71603531 5
 
0.1%
auem09200002 4
 
< 0.1%
ussm10904113 4
 
< 0.1%
gbum71029604 4
 
< 0.1%
uspr38619998 4
 
< 0.1%
usum71511919 4
 
< 0.1%
Other values (8938) 9950
99.5%
2024-06-13T11:15:36.021098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25127
20.9%
1 13170
 
11.0%
U 8278
 
6.9%
2 6739
 
5.6%
S 6435
 
5.4%
7 5768
 
4.8%
9 5346
 
4.5%
3 4833
 
4.0%
A 4680
 
3.9%
8 4519
 
3.8%
Other values (45) 35066
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 119961
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25127
20.9%
1 13170
 
11.0%
U 8278
 
6.9%
2 6739
 
5.6%
S 6435
 
5.4%
7 5768
 
4.8%
9 5346
 
4.5%
3 4833
 
4.0%
A 4680
 
3.9%
8 4519
 
3.8%
Other values (45) 35066
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 119961
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25127
20.9%
1 13170
 
11.0%
U 8278
 
6.9%
2 6739
 
5.6%
S 6435
 
5.4%
7 5768
 
4.8%
9 5346
 
4.5%
3 4833
 
4.0%
A 4680
 
3.9%
8 4519
 
3.8%
Other values (45) 35066
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 119961
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25127
20.9%
1 13170
 
11.0%
U 8278
 
6.9%
2 6739
 
5.6%
S 6435
 
5.4%
7 5768
 
4.8%
9 5346
 
4.5%
3 4833
 
4.0%
A 4680
 
3.9%
8 4519
 
3.8%
Other values (45) 35066
29.2%

Added By
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
spotify:user:bradnumber1
9999 

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters239976
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspotify:user:bradnumber1
2nd rowspotify:user:bradnumber1
3rd rowspotify:user:bradnumber1
4th rowspotify:user:bradnumber1
5th rowspotify:user:bradnumber1

Common Values

ValueCountFrequency (%)
spotify:user:bradnumber1 9999
100.0%

Length

2024-06-13T11:15:36.769518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-13T11:15:37.142848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
spotify:user:bradnumber1 9999
100.0%

Most occurring characters

ValueCountFrequency (%)
r 29997
12.5%
s 19998
 
8.3%
: 19998
 
8.3%
b 19998
 
8.3%
e 19998
 
8.3%
u 19998
 
8.3%
y 9999
 
4.2%
f 9999
 
4.2%
p 9999
 
4.2%
i 9999
 
4.2%
Other values (7) 69993
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 239976
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 29997
12.5%
s 19998
 
8.3%
: 19998
 
8.3%
b 19998
 
8.3%
e 19998
 
8.3%
u 19998
 
8.3%
y 9999
 
4.2%
f 9999
 
4.2%
p 9999
 
4.2%
i 9999
 
4.2%
Other values (7) 69993
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 239976
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 29997
12.5%
s 19998
 
8.3%
: 19998
 
8.3%
b 19998
 
8.3%
e 19998
 
8.3%
u 19998
 
8.3%
y 9999
 
4.2%
f 9999
 
4.2%
p 9999
 
4.2%
i 9999
 
4.2%
Other values (7) 69993
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 239976
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 29997
12.5%
s 19998
 
8.3%
: 19998
 
8.3%
b 19998
 
8.3%
e 19998
 
8.3%
u 19998
 
8.3%
y 9999
 
4.2%
f 9999
 
4.2%
p 9999
 
4.2%
i 9999
 
4.2%
Other values (7) 69993
29.2%
Distinct609
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
Minimum2020-03-05 09:20:20+00:00
Maximum2023-07-25 11:57:02+00:00
2024-06-13T11:15:37.400585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:37.693322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Artist Genres
Text

MISSING 

Distinct2815
Distinct (%)29.8%
Missing550
Missing (%)5.5%
Memory size78.2 KiB
2024-06-13T11:15:38.077638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length300
Median length159
Mean length43.32268
Min length3

Characters and Unicode

Total characters409356
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1526 ?
Unique (%)16.1%

Sample

1st rowacid house,ambient house,big beat,hip house
2nd rowdance pop,miami hip hop,pop
3rd rowdance pop,pop
4th rowalbum rock,art rock,british invasion,classic rock,folk rock,glam rock,protopunk,psychedelic rock,rock,singer-songwriter
5th rowalbum rock,british invasion,classic rock,rock
ValueCountFrequency (%)
pop 1794
 
4.6%
rock 1758
 
4.5%
australian 1333
 
3.4%
dance 1211
 
3.1%
hip 1127
 
2.9%
alternative 733
 
1.9%
pop,pop 703
 
1.8%
wave 652
 
1.7%
album 605
 
1.5%
rock,mellow 574
 
1.5%
Other values (2546) 28637
73.2%
2024-06-13T11:15:38.855452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 39924
 
9.8%
a 31468
 
7.7%
p 31219
 
7.6%
29678
 
7.2%
r 29487
 
7.2%
, 27609
 
6.7%
e 25310
 
6.2%
n 23205
 
5.7%
c 21274
 
5.2%
t 17680
 
4.3%
Other values (26) 132502
32.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 409356
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 39924
 
9.8%
a 31468
 
7.7%
p 31219
 
7.6%
29678
 
7.2%
r 29487
 
7.2%
, 27609
 
6.7%
e 25310
 
6.2%
n 23205
 
5.7%
c 21274
 
5.2%
t 17680
 
4.3%
Other values (26) 132502
32.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 409356
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 39924
 
9.8%
a 31468
 
7.7%
p 31219
 
7.6%
29678
 
7.2%
r 29487
 
7.2%
, 27609
 
6.7%
e 25310
 
6.2%
n 23205
 
5.7%
c 21274
 
5.2%
t 17680
 
4.3%
Other values (26) 132502
32.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 409356
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 39924
 
9.8%
a 31468
 
7.7%
p 31219
 
7.6%
29678
 
7.2%
r 29487
 
7.2%
, 27609
 
6.7%
e 25310
 
6.2%
n 23205
 
5.7%
c 21274
 
5.2%
t 17680
 
4.3%
Other values (26) 132502
32.4%

Danceability
Real number (ℝ)

HIGH CORRELATION 

Distinct779
Distinct (%)7.8%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.60792532
Minimum0
Maximum0.988
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:39.168308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.352
Q10.515
median0.617
Q30.71
95-th percentile0.8342
Maximum0.988
Range0.988
Interquartile range (IQR)0.195

Descriptive statistics

Standard deviation0.14586925
Coefficient of variation (CV)0.239946
Kurtosis-0.080969394
Mean0.60792532
Median Absolute Deviation (MAD)0.097
Skewness-0.31442586
Sum6077.4294
Variance0.021277838
MonotonicityNot monotonic
2024-06-13T11:15:39.484404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.672 39
 
0.4%
0.652 38
 
0.4%
0.653 37
 
0.4%
0.613 37
 
0.4%
0.551 35
 
0.4%
0.566 35
 
0.4%
0.646 35
 
0.4%
0.667 34
 
0.3%
0.562 34
 
0.3%
0.671 34
 
0.3%
Other values (769) 9639
96.4%
ValueCountFrequency (%)
0 1
< 0.1%
0.0994 1
< 0.1%
0.125 1
< 0.1%
0.128 1
< 0.1%
0.129 2
< 0.1%
0.135 1
< 0.1%
0.145 1
< 0.1%
0.149 1
< 0.1%
0.15 1
< 0.1%
0.153 1
< 0.1%
ValueCountFrequency (%)
0.988 1
 
< 0.1%
0.984 2
< 0.1%
0.98 1
 
< 0.1%
0.979 1
 
< 0.1%
0.978 1
 
< 0.1%
0.975 1
 
< 0.1%
0.97 2
< 0.1%
0.967 3
< 0.1%
0.965 2
< 0.1%
0.964 1
 
< 0.1%

Energy
Real number (ℝ)

HIGH CORRELATION 

Distinct876
Distinct (%)8.8%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.68328072
Minimum2.03 × 10-5
Maximum0.997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:39.769201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.03 × 10-5
5-th percentile0.3238
Q10.56
median0.712
Q30.835
95-th percentile0.943
Maximum0.997
Range0.9969797
Interquartile range (IQR)0.275

Descriptive statistics

Standard deviation0.1911315
Coefficient of variation (CV)0.27972617
Kurtosis-0.16960407
Mean0.68328072
Median Absolute Deviation (MAD)0.134
Skewness-0.63752258
Sum6830.7573
Variance0.036531249
MonotonicityNot monotonic
2024-06-13T11:15:40.051715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.874 33
 
0.3%
0.74 32
 
0.3%
0.672 31
 
0.3%
0.877 30
 
0.3%
0.836 30
 
0.3%
0.698 29
 
0.3%
0.795 29
 
0.3%
0.66 29
 
0.3%
0.702 28
 
0.3%
0.806 28
 
0.3%
Other values (866) 9698
97.0%
ValueCountFrequency (%)
2.03 × 10-51
< 0.1%
0.02 1
< 0.1%
0.0205 1
< 0.1%
0.0228 1
< 0.1%
0.0264 1
< 0.1%
0.0307 1
< 0.1%
0.0339 1
< 0.1%
0.0477 1
< 0.1%
0.0497 1
< 0.1%
0.0529 1
< 0.1%
ValueCountFrequency (%)
0.997 1
 
< 0.1%
0.994 4
< 0.1%
0.993 3
 
< 0.1%
0.992 2
 
< 0.1%
0.991 6
0.1%
0.99 3
 
< 0.1%
0.989 5
0.1%
0.988 8
0.1%
0.987 4
< 0.1%
0.986 1
 
< 0.1%

Key
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.1677503
Minimum0
Maximum11
Zeros1315
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:40.321899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5783921
Coefficient of variation (CV)0.69244679
Kurtosis-1.288366
Mean5.1677503
Median Absolute Deviation (MAD)3
Skewness0.029739749
Sum51662
Variance12.80489
MonotonicityNot monotonic
2024-06-13T11:15:40.527975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 1315
13.2%
7 1079
10.8%
9 1040
10.4%
2 1031
10.3%
1 909
9.1%
5 903
9.0%
4 803
8.0%
11 750
7.5%
6 633
6.3%
10 618
6.2%
Other values (2) 916
9.2%
ValueCountFrequency (%)
0 1315
13.2%
1 909
9.1%
2 1031
10.3%
3 301
 
3.0%
4 803
8.0%
5 903
9.0%
6 633
6.3%
7 1079
10.8%
8 615
6.2%
9 1040
10.4%
ValueCountFrequency (%)
11 750
7.5%
10 618
6.2%
9 1040
10.4%
8 615
6.2%
7 1079
10.8%
6 633
6.3%
5 903
9.0%
4 803
8.0%
3 301
 
3.0%
2 1031
10.3%

Loudness
Real number (ℝ)

HIGH CORRELATION 

Distinct6329
Distinct (%)63.3%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-7.2692175
Minimum-29.368
Maximum2.769
Zeros0
Zeros (%)0.0%
Negative9996
Negative (%)> 99.9%
Memory size78.2 KiB
2024-06-13T11:15:40.785994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-29.368
5-th percentile-13.6268
Q1-9.07
median-6.518
Q3-4.887
95-th percentile-3.1938
Maximum2.769
Range32.137
Interquartile range (IQR)4.183

Descriptive statistics

Standard deviation3.2817311
Coefficient of variation (CV)-0.4514559
Kurtosis1.2166208
Mean-7.2692175
Median Absolute Deviation (MAD)1.926
Skewness-1.0387791
Sum-72670.367
Variance10.769759
MonotonicityNot monotonic
2024-06-13T11:15:41.060239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.26 7
 
0.1%
-5.285 7
 
0.1%
-6.684 7
 
0.1%
-4.237 7
 
0.1%
-4.057 7
 
0.1%
-3.756 6
 
0.1%
-6.279 6
 
0.1%
-6.967 6
 
0.1%
-5.852 6
 
0.1%
-7.503 6
 
0.1%
Other values (6319) 9932
99.3%
ValueCountFrequency (%)
-29.368 1
< 0.1%
-25.42 1
< 0.1%
-23.309 1
< 0.1%
-23.242 1
< 0.1%
-23.092 1
< 0.1%
-23.032 1
< 0.1%
-22.602 1
< 0.1%
-22.304 1
< 0.1%
-22.138 1
< 0.1%
-21.861 1
< 0.1%
ValueCountFrequency (%)
2.769 1
< 0.1%
-0.276 1
< 0.1%
-0.358 1
< 0.1%
-0.418 1
< 0.1%
-0.682 1
< 0.1%
-0.776 1
< 0.1%
-0.81 1
< 0.1%
-0.861 1
< 0.1%
-1.059 1
< 0.1%
-1.09 1
< 0.1%

Mode
Categorical

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
1.0
6982 
0.0
3015 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters29991
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 6982
69.8%
0.0 3015
30.2%
(Missing) 2
 
< 0.1%

Length

2024-06-13T11:15:41.343812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-13T11:15:41.558260image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 6982
69.8%
0.0 3015
30.2%

Most occurring characters

ValueCountFrequency (%)
0 13012
43.4%
. 9997
33.3%
1 6982
23.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 13012
43.4%
. 9997
33.3%
1 6982
23.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 13012
43.4%
. 9997
33.3%
1 6982
23.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 13012
43.4%
. 9997
33.3%
1 6982
23.3%

Speechiness
Real number (ℝ)

Distinct1059
Distinct (%)10.6%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.065137641
Minimum0
Maximum0.711
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:41.783593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0272
Q10.0331
median0.0429
Q30.0675
95-th percentile0.197
Maximum0.711
Range0.711
Interquartile range (IQR)0.0344

Descriptive statistics

Standard deviation0.061323842
Coefficient of variation (CV)0.94145014
Kurtosis13.069823
Mean0.065137641
Median Absolute Deviation (MAD)0.0123
Skewness3.261783
Sum651.181
Variance0.0037606136
MonotonicityNot monotonic
2024-06-13T11:15:42.066409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0321 53
 
0.5%
0.0305 52
 
0.5%
0.0295 47
 
0.5%
0.0308 46
 
0.5%
0.0294 46
 
0.5%
0.0311 46
 
0.5%
0.0316 45
 
0.5%
0.0298 44
 
0.4%
0.0325 43
 
0.4%
0.0277 43
 
0.4%
Other values (1049) 9532
95.3%
ValueCountFrequency (%)
0 1
< 0.1%
0.0218 1
< 0.1%
0.0224 1
< 0.1%
0.0225 2
< 0.1%
0.0226 1
< 0.1%
0.0227 1
< 0.1%
0.0228 1
< 0.1%
0.023 1
< 0.1%
0.0231 2
< 0.1%
0.0232 2
< 0.1%
ValueCountFrequency (%)
0.711 1
< 0.1%
0.533 1
< 0.1%
0.526 1
< 0.1%
0.519 1
< 0.1%
0.516 1
< 0.1%
0.512 1
< 0.1%
0.499 2
< 0.1%
0.486 1
< 0.1%
0.481 1
< 0.1%
0.473 1
< 0.1%

Acousticness
Real number (ℝ)

HIGH CORRELATION 

Distinct2746
Distinct (%)27.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.20858866
Minimum2.72 × 10-6
Maximum0.991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:42.383147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.72 × 10-6
5-th percentile0.00088
Q10.0184
median0.0956
Q30.318
95-th percentile0.761
Maximum0.991
Range0.99099728
Interquartile range (IQR)0.2996

Descriptive statistics

Standard deviation0.24884208
Coefficient of variation (CV)1.1929799
Kurtosis0.58144955
Mean0.20858866
Median Absolute Deviation (MAD)0.09063
Skewness1.2968683
Sum2085.2608
Variance0.06192238
MonotonicityNot monotonic
2024-06-13T11:15:42.687642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.107 28
 
0.3%
0.157 25
 
0.3%
0.117 24
 
0.2%
0.113 24
 
0.2%
0.103 22
 
0.2%
0.11 22
 
0.2%
0.13 21
 
0.2%
0.112 21
 
0.2%
0.119 20
 
0.2%
0.156 20
 
0.2%
Other values (2736) 9770
97.7%
ValueCountFrequency (%)
2.72 × 10-61
< 0.1%
5.63 × 10-61
< 0.1%
8.71 × 10-61
< 0.1%
8.86 × 10-61
< 0.1%
1.1 × 10-52
< 0.1%
1.17 × 10-51
< 0.1%
1.23 × 10-51
< 0.1%
1.24 × 10-51
< 0.1%
1.25 × 10-51
< 0.1%
1.32 × 10-51
< 0.1%
ValueCountFrequency (%)
0.991 1
 
< 0.1%
0.987 1
 
< 0.1%
0.984 1
 
< 0.1%
0.979 1
 
< 0.1%
0.978 1
 
< 0.1%
0.977 3
< 0.1%
0.972 1
 
< 0.1%
0.971 2
< 0.1%
0.968 1
 
< 0.1%
0.967 1
 
< 0.1%

Instrumentalness
Real number (ℝ)

ZEROS 

Distinct3028
Distinct (%)30.3%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.029331321
Minimum0
Maximum0.985
Zeros3996
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:42.973732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.69 × 10-6
Q30.000561
95-th percentile0.149
Maximum0.985
Range0.985
Interquartile range (IQR)0.000561

Descriptive statistics

Standard deviation0.12357638
Coefficient of variation (CV)4.21312
Kurtosis28.337095
Mean0.029331321
Median Absolute Deviation (MAD)5.69 × 10-6
Skewness5.2405586
Sum293.22522
Variance0.015271121
MonotonicityNot monotonic
2024-06-13T11:15:43.254639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3996
40.0%
1.16 × 10-615
 
0.2%
1.64 × 10-611
 
0.1%
1.22 × 10-511
 
0.1%
1.21 × 10-611
 
0.1%
1.33 × 10-610
 
0.1%
1.65 × 10-610
 
0.1%
1.11 × 10-610
 
0.1%
0.000115 10
 
0.1%
1.16 × 10-59
 
0.1%
Other values (3018) 5904
59.0%
ValueCountFrequency (%)
0 3996
40.0%
1.01 × 10-66
 
0.1%
1.02 × 10-69
 
0.1%
1.03 × 10-68
 
0.1%
1.04 × 10-63
 
< 0.1%
1.05 × 10-61
 
< 0.1%
1.06 × 10-62
 
< 0.1%
1.07 × 10-62
 
< 0.1%
1.08 × 10-65
 
0.1%
1.09 × 10-65
 
0.1%
ValueCountFrequency (%)
0.985 1
< 0.1%
0.973 1
< 0.1%
0.964 1
< 0.1%
0.959 1
< 0.1%
0.957 1
< 0.1%
0.955 1
< 0.1%
0.949 2
< 0.1%
0.944 2
< 0.1%
0.935 1
< 0.1%
0.934 1
< 0.1%

Liveness
Real number (ℝ)

Distinct1361
Distinct (%)13.6%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.18577738
Minimum0.012
Maximum0.989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:43.565245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.012
5-th percentile0.0526
Q10.0892
median0.128
Q30.245
95-th percentile0.4772
Maximum0.989
Range0.977
Interquartile range (IQR)0.1558

Descriptive statistics

Standard deviation0.14919361
Coefficient of variation (CV)0.80307735
Kurtosis5.3264574
Mean0.18577738
Median Absolute Deviation (MAD)0.053
Skewness2.0802079
Sum1857.2165
Variance0.022258733
MonotonicityNot monotonic
2024-06-13T11:15:43.861252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.105 95
 
1.0%
0.104 87
 
0.9%
0.11 87
 
0.9%
0.114 80
 
0.8%
0.107 76
 
0.8%
0.102 76
 
0.8%
0.101 74
 
0.7%
0.111 71
 
0.7%
0.113 71
 
0.7%
0.109 71
 
0.7%
Other values (1351) 9209
92.1%
ValueCountFrequency (%)
0.012 1
< 0.1%
0.0165 1
< 0.1%
0.0175 2
< 0.1%
0.0185 1
< 0.1%
0.0188 1
< 0.1%
0.021 1
< 0.1%
0.0215 2
< 0.1%
0.0219 1
< 0.1%
0.0233 1
< 0.1%
0.0234 1
< 0.1%
ValueCountFrequency (%)
0.989 1
< 0.1%
0.982 1
< 0.1%
0.98 1
< 0.1%
0.979 2
< 0.1%
0.977 1
< 0.1%
0.973 1
< 0.1%
0.97 1
< 0.1%
0.966 2
< 0.1%
0.965 1
< 0.1%
0.96 1
< 0.1%

Valence
Real number (ℝ)

Distinct994
Distinct (%)9.9%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.58545892
Minimum0
Maximum0.995
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:44.149031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1778
Q10.398
median0.598
Q30.783
95-th percentile0.951
Maximum0.995
Range0.995
Interquartile range (IQR)0.385

Descriptive statistics

Standard deviation0.23910471
Coefficient of variation (CV)0.40840562
Kurtosis-0.95744942
Mean0.58545892
Median Absolute Deviation (MAD)0.192
Skewness-0.19771548
Sum5852.8328
Variance0.057171064
MonotonicityNot monotonic
2024-06-13T11:15:44.469403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.961 55
 
0.6%
0.963 46
 
0.5%
0.962 45
 
0.5%
0.964 37
 
0.4%
0.96 36
 
0.4%
0.965 35
 
0.4%
0.967 28
 
0.3%
0.761 26
 
0.3%
0.638 25
 
0.3%
0.971 24
 
0.2%
Other values (984) 9640
96.4%
ValueCountFrequency (%)
0 1
< 0.1%
0.0334 1
< 0.1%
0.035 2
< 0.1%
0.0354 1
< 0.1%
0.0376 1
< 0.1%
0.0381 1
< 0.1%
0.0382 2
< 0.1%
0.0387 1
< 0.1%
0.0393 1
< 0.1%
0.0394 1
< 0.1%
ValueCountFrequency (%)
0.995 1
 
< 0.1%
0.991 1
 
< 0.1%
0.99 1
 
< 0.1%
0.988 1
 
< 0.1%
0.987 1
 
< 0.1%
0.985 3
< 0.1%
0.984 1
 
< 0.1%
0.983 1
 
< 0.1%
0.982 2
< 0.1%
0.98 4
< 0.1%

Tempo
Real number (ℝ)

HIGH CORRELATION 

Distinct8621
Distinct (%)86.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean121.49665
Minimum0
Maximum217.913
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2024-06-13T11:15:44.757869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile81.3256
Q1102.642
median120.653
Q3134.328
95-th percentile172.6644
Maximum217.913
Range217.913
Interquartile range (IQR)31.686

Descriptive statistics

Standard deviation26.260686
Coefficient of variation (CV)0.21614329
Kurtosis0.30434342
Mean121.49665
Median Absolute Deviation (MAD)15.887
Skewness0.52858755
Sum1214602
Variance689.62364
MonotonicityNot monotonic
2024-06-13T11:15:45.026451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.998 6
 
0.1%
120.032 6
 
0.1%
127.96 6
 
0.1%
125.983 6
 
0.1%
127.993 5
 
0.1%
127.997 5
 
0.1%
120.003 5
 
0.1%
120.048 5
 
0.1%
127.99 5
 
0.1%
100.021 5
 
0.1%
Other values (8611) 9943
99.4%
ValueCountFrequency (%)
0 1
< 0.1%
34.999 1
< 0.1%
50.937 1
< 0.1%
54.282 1
< 0.1%
55.305 1
< 0.1%
59.406 1
< 0.1%
60.03 1
< 0.1%
60.197 1
< 0.1%
60.3 1
< 0.1%
61.007 1
< 0.1%
ValueCountFrequency (%)
217.913 1
< 0.1%
215.537 1
< 0.1%
213.654 1
< 0.1%
210.796 1
< 0.1%
210.78 1
< 0.1%
209.591 1
< 0.1%
208.571 1
< 0.1%
208.282 1
< 0.1%
207.966 1
< 0.1%
207.673 1
< 0.1%

Time Signature
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Memory size78.2 KiB
4.0
9527 
3.0
 
390
5.0
 
59
1.0
 
20
0.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters29991
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row4.0
2nd row4.0
3rd row4.0
4th row4.0
5th row4.0

Common Values

ValueCountFrequency (%)
4.0 9527
95.3%
3.0 390
 
3.9%
5.0 59
 
0.6%
1.0 20
 
0.2%
0.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2024-06-13T11:15:45.275909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-13T11:15:45.522363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4.0 9527
95.3%
3.0 390
 
3.9%
5.0 59
 
0.6%
1.0 20
 
0.2%
0.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 9998
33.3%
. 9997
33.3%
4 9527
31.8%
3 390
 
1.3%
5 59
 
0.2%
1 20
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 9998
33.3%
. 9997
33.3%
4 9527
31.8%
3 390
 
1.3%
5 59
 
0.2%
1 20
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 9998
33.3%
. 9997
33.3%
4 9527
31.8%
3 390
 
1.3%
5 59
 
0.2%
1 20
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29991
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 9998
33.3%
. 9997
33.3%
4 9527
31.8%
3 390
 
1.3%
5 59
 
0.2%
1 20
 
0.1%

Album Genres
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9999
Missing (%)100.0%
Memory size78.2 KiB

Label
Text

Distinct1465
Distinct (%)14.7%
Missing6
Missing (%)0.1%
Memory size78.2 KiB
2024-06-13T11:15:45.956214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length69
Median length53
Mean length16.25758
Min length2

Characters and Unicode

Total characters162462
Distinct characters85
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)7.7%

Sample

1st rowJams Communications
2nd rowMr.305/Polo Grounds Music/J Records
3rd rowJive
4th rowSanctuary Records
5th rowUniversal Music Group
ValueCountFrequency (%)
records 2617
 
11.3%
music 2417
 
10.4%
universal 1482
 
6.4%
group 937
 
4.1%
australia 634
 
2.7%
ltd 499
 
2.2%
uk 489
 
2.1%
columbia 469
 
2.0%
sony 419
 
1.8%
entertainment 387
 
1.7%
Other values (1732) 12781
55.3%
2024-06-13T11:15:46.838393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13138
 
8.1%
e 11462
 
7.1%
r 10589
 
6.5%
i 10525
 
6.5%
s 9877
 
6.1%
o 9696
 
6.0%
a 9640
 
5.9%
c 8110
 
5.0%
n 7979
 
4.9%
l 6798
 
4.2%
Other values (75) 64648
39.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 162462
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
13138
 
8.1%
e 11462
 
7.1%
r 10589
 
6.5%
i 10525
 
6.5%
s 9877
 
6.1%
o 9696
 
6.0%
a 9640
 
5.9%
c 8110
 
5.0%
n 7979
 
4.9%
l 6798
 
4.2%
Other values (75) 64648
39.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 162462
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
13138
 
8.1%
e 11462
 
7.1%
r 10589
 
6.5%
i 10525
 
6.5%
s 9877
 
6.1%
o 9696
 
6.0%
a 9640
 
5.9%
c 8110
 
5.0%
n 7979
 
4.9%
l 6798
 
4.2%
Other values (75) 64648
39.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 162462
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
13138
 
8.1%
e 11462
 
7.1%
r 10589
 
6.5%
i 10525
 
6.5%
s 9877
 
6.1%
o 9696
 
6.0%
a 9640
 
5.9%
c 8110
 
5.0%
n 7979
 
4.9%
l 6798
 
4.2%
Other values (75) 64648
39.8%
Distinct5378
Distinct (%)53.9%
Missing24
Missing (%)0.2%
Memory size78.2 KiB
2024-06-13T11:15:47.406945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length974
Median length362
Mean length93.731529
Min length12

Characters and Unicode

Total characters934972
Distinct characters103
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3505 ?
Unique (%)35.1%

Sample

1st rowC 1992 Copyright Control, P 1992 Jams Communications
2nd rowP (P) 2009 RCA/JIVE Label Group, a unit of Sony Music Entertainment
3rd rowP (P) 1999 Zomba Recording LLC
4th rowC © 2014 Sanctuary Records Group Ltd., a BMG Company, P ℗ 2014 Sanctuary Records Group Ltd., a BMG Company
5th rowC © 2002 ABKCO Music & Records Inc., P ℗ 2002 ABKCO Music & Records Inc.
ValueCountFrequency (%)
p 12699
 
7.8%
records 8285
 
5.1%
c 7807
 
4.8%
music 7510
 
4.6%
© 5658
 
3.5%
â„— 5644
 
3.4%
inc 3977
 
2.4%
a 3746
 
2.3%
ltd 3612
 
2.2%
of 3248
 
2.0%
Other values (2618) 101416
62.0%
2024-06-13T11:15:48.584656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153627
 
16.4%
e 57570
 
6.2%
i 49933
 
5.3%
n 48068
 
5.1%
o 44564
 
4.8%
r 43154
 
4.6%
t 40944
 
4.4%
s 38021
 
4.1%
a 34858
 
3.7%
c 34052
 
3.6%
Other values (93) 390181
41.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 934972
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
153627
 
16.4%
e 57570
 
6.2%
i 49933
 
5.3%
n 48068
 
5.1%
o 44564
 
4.8%
r 43154
 
4.6%
t 40944
 
4.4%
s 38021
 
4.1%
a 34858
 
3.7%
c 34052
 
3.6%
Other values (93) 390181
41.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 934972
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
153627
 
16.4%
e 57570
 
6.2%
i 49933
 
5.3%
n 48068
 
5.1%
o 44564
 
4.8%
r 43154
 
4.6%
t 40944
 
4.4%
s 38021
 
4.1%
a 34858
 
3.7%
c 34052
 
3.6%
Other values (93) 390181
41.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 934972
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
153627
 
16.4%
e 57570
 
6.2%
i 49933
 
5.3%
n 48068
 
5.1%
o 44564
 
4.8%
r 43154
 
4.6%
t 40944
 
4.4%
s 38021
 
4.1%
a 34858
 
3.7%
c 34052
 
3.6%
Other values (93) 390181
41.7%

Interactions

2024-06-13T11:15:08.556752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:17.617805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:21.095603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:24.975060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:29.550456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:33.217308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:36.708937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:41.044787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:45.024023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:48.570833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:52.211606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:57.103551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:00.518322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:04.016593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:08.929204image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:17.869269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:21.340860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:25.335764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:29.809817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:33.495181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:36.957462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:41.751747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:45.278340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:48.828988image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:52.956731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:57.337412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:00.769387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:04.258930image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:09.265592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:18.103434image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:21.587600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:25.709734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:30.033149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:33.732436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:37.181692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:42.050240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:45.516265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:49.085106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:53.322104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:57.589370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:01.004297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:04.491464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:09.646933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:18.379317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:21.858093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:26.069264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:30.313604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:33.993972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:37.457928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:42.317110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:45.781948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:49.362269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:53.694765image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:57.838731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:01.260082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:04.769462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:09.884976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:18.623657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:22.076790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:26.412484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:30.554014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:34.231698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:37.714972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:42.574446image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:46.041556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:49.618491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:54.052961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:58.072350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:01.511703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:05.003906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:10.128188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:18.866238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:22.340649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:26.773073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:30.802841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:34.492940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:37.942736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:42.821912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:46.288689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:49.862556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:54.457143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:58.306731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:01.762918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:05.244867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:10.377274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:19.101514image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:22.584580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:27.121281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:31.029905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:34.735523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:38.176673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:43.044327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:46.554404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:50.123910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:54.779190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:58.570887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:02.001260image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:05.497207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:10.610137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:19.337904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:22.813438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:27.532042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:31.281934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:34.974153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:38.498999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:43.282485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:46.798574image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:50.375616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:55.127603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:58.807128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:02.247050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:05.738897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:10.855747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:19.614343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:23.263749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:27.915953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:31.747462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:35.231282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:38.869476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:43.554380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:47.050273image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:50.632104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:55.491554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:59.044037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:02.529323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:06.002188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:11.123933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:19.892569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:23.522323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:28.289455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:32.003913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:35.508404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:39.251945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:43.808485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:47.306829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:50.891781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:55.915088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:59.298485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:02.798957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:06.338666image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:11.381609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:20.132620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:23.757814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:28.558489image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:32.258580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:35.745059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:39.636251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:44.048176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:47.562733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:51.154401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:56.156221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:59.558792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:03.039905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:06.657125image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:11.620381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:20.391111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:23.998517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:28.805476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:32.519586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:35.979603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:39.994004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:44.288440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:47.811780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:51.418564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:56.408889image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:59.793290image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:03.276714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:07.015966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:11.852444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:20.624849image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:24.280392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:29.050037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:32.758971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:36.224142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:40.386366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:44.552205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:48.070570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:51.667021image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:56.648887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:00.032812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:03.534691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:07.878911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:12.096944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:20.878802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:24.654211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:29.308018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:32.991305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:36.483100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:40.713794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:44.796542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:48.320007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:51.918345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:14:56.878006image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:00.260112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:03.782698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-13T11:15:08.219071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-06-13T11:15:49.024049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
AcousticnessDanceabilityDisc NumberEnergyExplicitInstrumentalnessKeyLivenessLoudnessModePopularitySpeechinessTempoTime SignatureTrack Duration (ms)Track NumberValence
Acousticness1.000-0.0680.023-0.5540.068-0.166-0.018-0.015-0.4160.1360.008-0.179-0.1460.130-0.1720.082-0.049
Danceability-0.0681.000-0.0080.0720.1720.0250.000-0.1310.0710.1280.0580.203-0.1450.513-0.035-0.0980.442
Disc Number0.023-0.0081.000-0.0030.0000.0290.0100.024-0.0330.014-0.041-0.019-0.0090.018-0.0070.0800.037
Energy-0.5540.072-0.0031.0000.0700.0940.0340.1200.6460.119-0.0080.3290.2000.1380.046-0.0750.259
Explicit0.0680.1720.0000.0701.000-0.0950.0100.0040.1050.0410.0610.179-0.0230.0410.0440.010-0.001
Instrumentalness-0.1660.0250.0290.094-0.0951.0000.012-0.034-0.1850.009-0.040-0.0840.0530.0000.1480.0340.052
Key-0.0180.0000.0100.0340.0100.0121.000-0.0070.0150.2360.0110.0400.0070.0270.011-0.0040.002
Liveness-0.015-0.1310.0240.1200.004-0.034-0.0071.0000.0700.000-0.0340.0530.0260.009-0.0400.014-0.032
Loudness-0.4160.071-0.0330.6460.105-0.1850.0150.0701.0000.1170.0350.2520.0970.075-0.032-0.1130.001
Mode0.1360.1280.0140.1190.0410.0090.2360.0000.1171.000-0.016-0.125-0.0010.053-0.0420.047-0.018
Popularity0.0080.058-0.041-0.0080.061-0.0400.011-0.0340.035-0.0161.0000.024-0.0130.0110.018-0.069-0.006
Speechiness-0.1790.203-0.0190.3290.179-0.0840.0400.0530.252-0.1250.0241.0000.1280.061-0.071-0.0740.124
Tempo-0.146-0.145-0.0090.200-0.0230.0530.0070.0260.097-0.001-0.0130.1281.0000.503-0.003-0.0200.064
Time Signature0.1300.5130.0180.1380.0410.0000.0270.0090.0750.0530.0110.0610.5031.0000.044-0.0340.130
Track Duration (ms)-0.172-0.035-0.0070.0460.0440.1480.011-0.040-0.032-0.0420.018-0.071-0.0030.0441.0000.090-0.208
Track Number0.082-0.0980.080-0.0750.0100.034-0.0040.014-0.1130.047-0.069-0.074-0.020-0.0340.0901.000-0.010
Valence-0.0490.4420.0370.259-0.0010.0520.002-0.0320.001-0.018-0.0060.1240.0640.130-0.208-0.0101.000

Missing values

2024-06-13T11:15:12.541348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-13T11:15:13.531968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-06-13T11:15:14.420098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Track URITrack NameArtist URI(s)Artist Name(s)Album URIAlbum NameAlbum Artist URI(s)Album Artist Name(s)Album Release DateAlbum Image URLDisc NumberTrack NumberTrack Duration (ms)Track Preview URLExplicitPopularityISRCAdded ByAdded AtArtist GenresDanceabilityEnergyKeyLoudnessModeSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoTime SignatureAlbum GenresLabelCopyrights
0spotify:track:1XAZlnVtthcDZt2NI1DtxoJustified & Ancient - Stand by the Jamsspotify:artist:6dYrdRlNZSKaVxYg5IrvCHThe KLFspotify:album:4MC0ZjNtVP1nDD5lsLxFjcSongs Collectionspotify:artist:6dYrdRlNZSKaVxYg5IrvCHThe KLF1992-08-03https://i.scdn.co/image/ab67616d0000b27355346bc1f268730f607f954413216270NaNFalse0QMARG1760056spotify:user:bradnumber12020-03-05T09:20:39Zacid house,ambient house,big beat,hip house0.6170.8728.0-12.3051.00.04800.01580.1120000.40800.504111.4584.0NaNJams CommunicationsC 1992 Copyright Control, P 1992 Jams Communications
1spotify:track:6a8GbQIlV8HBUW3c6Uk9PHI Know You Want Me (Calle Ocho)spotify:artist:0TnOYISbd1XYRBk9myasegPitbullspotify:album:5xLAcbvbSAlRtPXnKkggXAPitbull Starring In Rebelutionspotify:artist:0TnOYISbd1XYRBk9myasegPitbull2009-10-23https://i.scdn.co/image/ab67616d0000b27326d73ab8423a350faa5d395a13237120https://p.scdn.co/mp3-preview/d6f8883fc955cb0ecb7f3e1e06e77a9d8611158d?cid=9950ac751e34487dbbe027c4fd7f8e99False64USJAY0900144spotify:user:bradnumber12021-08-08T09:26:31Zdance pop,miami hip hop,pop0.8250.7432.0-5.9951.00.14900.01420.0000210.23700.800127.0454.0NaNMr.305/Polo Grounds Music/J RecordsP (P) 2009 RCA/JIVE Label Group, a unit of Sony Music Entertainment
2spotify:track:70XtWbcVZcpaOddJftMcViFrom the Bottom of My Broken Heartspotify:artist:26dSoYclwsYLMAKD3tpOr4Britney Spearsspotify:album:3WNxdumkSMGMJRhEgK80qx...Baby One More Time (Digital Deluxe Version)spotify:artist:26dSoYclwsYLMAKD3tpOr4Britney Spears1999-01-12https://i.scdn.co/image/ab67616d0000b2738e49866860c25afffe2f1a0216312533https://p.scdn.co/mp3-preview/1de5faef947224dcb7efb26a5303ae0735b28167?cid=9950ac751e34487dbbe027c4fd7f8e99False56USJI19910455spotify:user:bradnumber12021-08-08T09:26:31Zdance pop,pop0.6770.6657.0-5.1711.00.03050.56000.0000010.33800.70674.9814.0NaNJiveP (P) 1999 Zomba Recording LLC
3spotify:track:1NXUWyPJk5kO6DQJ5t7bDuApeman - 2014 Remastered Versionspotify:artist:1SQRv42e4PjEYfPhS0Tk9EThe Kinksspotify:album:6lL6HugNEN4Vlc8sj0ZcseLola vs. Powerman and the Moneygoround, Pt. One + Percy (Super Deluxe)spotify:artist:1SQRv42e4PjEYfPhS0Tk9EThe Kinks2014-10-20https://i.scdn.co/image/ab67616d0000b2731e7c5307ccbbb74101e0cc77111233400https://p.scdn.co/mp3-preview/c4df3a832509cc5506bd0c91419146f78d864825?cid=9950ac751e34487dbbe027c4fd7f8e99False42GB5KW1499822spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,art rock,british invasion,classic rock,folk rock,glam rock,protopunk,psychedelic rock,rock,singer-songwriter0.6830.7289.0-8.9201.00.25900.56800.0000510.03840.83375.3114.0NaNSanctuary RecordsC © 2014 Sanctuary Records Group Ltd., a BMG Company, P ℗ 2014 Sanctuary Records Group Ltd., a BMG Company
4spotify:track:72WZtWs6V7uu3aMgMmEkYeYou Can't Always Get What You Wantspotify:artist:22bE4uQ6baNwSHPVcDxLCeThe Rolling Stonesspotify:album:0c78nsgqX6VfniSNWIxwoDLet It Bleedspotify:artist:22bE4uQ6baNwSHPVcDxLCeThe Rolling Stones1969-12-05https://i.scdn.co/image/ab67616d0000b27373d92707b0e7da0c493f5b8619448720NaNFalse0USA176910100spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,british invasion,classic rock,rock0.3190.6270.0-9.6111.00.06870.67500.0000730.28900.49785.8184.0NaNUniversal Music GroupC © 2002 ABKCO Music & Records Inc., P ℗ 2002 ABKCO Music & Records Inc.
5spotify:track:4bEb3KE4mSKlTFjtWJQBqODon't Stop - 2004 Remasterspotify:artist:08GQAI4eElDnROBrJRGE0XFleetwood Macspotify:album:1bt6q2SruMsBtcerNVtpZBRumoursspotify:artist:08GQAI4eElDnROBrJRGE0XFleetwood Mac1977-02-04https://i.scdn.co/image/ab67616d0000b27357df7ce0eac715cf70e519a714193346https://p.scdn.co/mp3-preview/64b1e9388ec19f29fa36d38d1f80f56d77df56a3?cid=9950ac751e34487dbbe027c4fd7f8e99False79USWB10400049spotify:user:bradnumber12022-08-31T00:08:18Zalbum rock,classic rock,rock,soft rock,yacht rock0.6710.7109.0-7.7241.00.03560.03930.0000110.03870.834118.7454.0NaNRhino/Warner RecordsC © 2004 Warner Records Inc., P ℗ 2004 Warner Records Inc.
6spotify:track:0d2iYfpKoM0QCKvcLCkBaoEastside (with Halsey & Khalid)spotify:artist:5CiGnKThu5ctn9pBxv7DGa, spotify:artist:26VFTg2z8YR0cCuwLzESi2, spotify:artist:6LuN9FCkKOj5PcnpouEgnybenny blanco, Halsey, Khalidspotify:album:7pkLXlFdpQDfmHujT2AbBKEastside (with Halsey & Khalid)spotify:artist:5CiGnKThu5ctn9pBxv7DGa, spotify:artist:26VFTg2z8YR0cCuwLzESi2, spotify:artist:6LuN9FCkKOj5PcnpouEgnybenny blanco, Halsey, Khalid2018-07-12https://i.scdn.co/image/ab67616d0000b2733154f0bdf9a17385d7afc6ba11173799https://p.scdn.co/mp3-preview/24726be4c89b67eab298a72560b637581450421c?cid=9950ac751e34487dbbe027c4fd7f8e99False78USUM71809132spotify:user:bradnumber12021-08-08T09:26:31Zpop,electropop,etherpop,indie poptimism,pop,pop,pop r&b0.5600.6806.0-7.6480.00.32100.55500.0000000.11600.31989.3914.0NaNBenny Blanco Solo Album PSC © 2018 Friends Keep Secrets/Interscope Records, P ℗ 2018 Friends Keep Secrets/Interscope Records
7spotify:track:5LjSxAIKwyZvQqJ04ZQ0DaSomething About The Way You Look Tonight - Edit Versionspotify:artist:3PhoLpVuITZKcymswpck5bElton Johnspotify:album:3g61rwvRs1NPeVBxuAMmHZCandle In The Wind 1997 / Something About ...spotify:artist:3PhoLpVuITZKcymswpck5bElton John1997-01-01https://i.scdn.co/image/ab67616d0000b27352a56df14c3a5e318925787c11240546https://p.scdn.co/mp3-preview/3e5a8a62babcf10b5b4d11d1485f4ed452dbdc7b?cid=9950ac751e34487dbbe027c4fd7f8e99False61GBAMS9700013spotify:user:bradnumber12021-08-08T09:26:31Zglam rock,mellow gold,piano rock,rock0.4800.6286.0-7.6431.00.02620.17400.0000330.07530.541143.4124.0NaNEMIC © 1997 Mercury Records Limited, P This Compilation ℗ 1997 Mercury Records Limited
8spotify:track:00qOE7OjRl0BpYiCiweZB2Juke Box Herospotify:artist:6IRouO5mvvfcyxtPDKMYFNForeignerspotify:album:2Pw51hAGvWpTA3AYl2WVuu4 (Expanded)spotify:artist:6IRouO5mvvfcyxtPDKMYFNForeigner1981https://i.scdn.co/image/ab67616d0000b27362d48acfd5073491df46f7ac12259800https://p.scdn.co/mp3-preview/2353bb343dd4f1872d954b1603587597e9258630?cid=9950ac751e34487dbbe027c4fd7f8e99False74USAT20803006spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,classic rock,glam metal,hard rock,heartland rock,mellow gold,rock,soft rock0.3570.6539.0-5.5541.00.06540.08280.0000000.08440.522176.6474.0NaNRhino AtlanticC © 2002 Atlantic Recording Corp., marketed by Rhino Entertainment Company, a Warner Music Group company, P ℗ 2002 Atlantic Recording Corp.
9spotify:track:3OalxlWH0v14kyBcNBMINtMercyspotify:artist:7n2wHs1TKAczGzO7Dd2rGrShawn Mendesspotify:album:0S9QJQiRmG9JYYfJfKqhDFIlluminate (Deluxe)spotify:artist:7n2wHs1TKAczGzO7Dd2rGrShawn Mendes2016-09-23https://i.scdn.co/image/ab67616d0000b2738a24ed638eedd60514a789ef12208733NaNFalse0USUM71603531spotify:user:bradnumber12021-08-08T09:26:31Zcanadian pop,pop,viral pop0.5620.68111.0-4.9340.00.08710.11300.0000000.11000.357148.0644.0NaNUniversal Music GroupC © 2016 Island Records, a division of UMG Recordings, Inc., P ℗ 2016 Island Records, a division of UMG Recordings, Inc.
Track URITrack NameArtist URI(s)Artist Name(s)Album URIAlbum NameAlbum Artist URI(s)Album Artist Name(s)Album Release DateAlbum Image URLDisc NumberTrack NumberTrack Duration (ms)Track Preview URLExplicitPopularityISRCAdded ByAdded AtArtist GenresDanceabilityEnergyKeyLoudnessModeSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoTime SignatureAlbum GenresLabelCopyrights
9989spotify:track:39JofJHEtg8I4fSyo7ImftB.O.T.A. (Baddest Of Them All) - Editspotify:artist:4XC335ouK6pXyq4QiIb8bP, spotify:artist:6uJ51uV5rYzu1MJkC4CceIEliza Rose, Interplanetary Criminalspotify:album:2lQgd3Svp1ZWAzZPLobAPKB.O.T.A. (Baddest Of Them All)spotify:artist:4XC335ouK6pXyq4QiIb8bP, spotify:artist:6uJ51uV5rYzu1MJkC4CceIEliza Rose, Interplanetary Criminal2022-08-12https://i.scdn.co/image/ab67616d0000b273eb15b994e15a3a6634d1694e11226626https://p.scdn.co/mp3-preview/475c0c2a67c6db3c8f66264e04eb3fa9d3a7a0ba?cid=9950ac751e34487dbbe027c4fd7f8e99False82QZAKB2166405spotify:user:bradnumber12023-07-09T01:59:43Zhouse,breaks,experimental house0.7360.9060.0-7.5891.00.04800.1640000.5850000.10600.698137.0014.0NaNWarner RecordsC Under exclusive licence to Warner Music UK Limited, © 2022 One House X Limited, P Under exclusive licence to Warner Music UK Limited, ℗ 2022 One House X Limited
9990spotify:track:4gFL3QgCRx0o1B5KjlkCR1Get A Lifespotify:artist:0zg9mF9dX2knvdTKnL22T1Freestylersspotify:album:35FjWueXGCUxGAOIface7ORaw As F**kspotify:artist:0zg9mF9dX2knvdTKnL22T1Freestylers2004-03-26https://i.scdn.co/image/ab67616d0000b2735f2f359ef02665ac26599ba414312720https://p.scdn.co/mp3-preview/e617ef6662d3e1d9a0d4d45b4a10c30f38d17351?cid=9950ac751e34487dbbe027c4fd7f8e99False22GBFNF0300017spotify:user:bradnumber12023-07-10T04:13:07Zbig beat,breakbeat0.7100.95211.0-6.2860.00.05570.0232000.0001210.28600.889137.9764.0NaNAltra Moda MusicC 2004 Altra Moda Music, P 2004 Altra Moda Music
9991spotify:track:3AjSfp5FDvwtMU9XBsbS8jPush Up - Main Editspotify:artist:2gW0M5fn2r7Lo4Hn1r8HZ5Creedsspotify:album:3v5BP6gPT1nNU9rjs57fF0Push Up (Main Edit)spotify:artist:2gW0M5fn2r7Lo4Hn1r8HZ5Creeds2023-03-31https://i.scdn.co/image/ab67616d0000b273b1f8e7c90fbffff33cb7425411139300https://p.scdn.co/mp3-preview/b7bd7fa2bdcb29f456bdc684885b56fa091efd64?cid=9950ac751e34487dbbe027c4fd7f8e99False86DEE862300564spotify:user:bradnumber12023-07-11T01:16:38ZNaN0.7670.8307.0-8.7801.00.20600.2090000.8360000.05820.18775.0234.0NaNColumbia/B1 RecordingsP (P) 2023 Rave Alert Records, under exclusive license to Ministry of Sound/Arista Records/B1 Recordings GmbH, a Sony Music Entertainment company.
9992spotify:track:3BKD1PwArikchz2Zrlp1qiBaby Don't Hurt Mespotify:artist:1Cs0zKBU1kc0i8ypK3B9ai, spotify:artist:1zNqDE7qDGCsyzJwohVaoX, spotify:artist:6AMd49uBDJfhf30Ak2QR5sDavid Guetta, Anne-Marie, Coi Lerayspotify:album:327tc3Eruk1HP1w62iqROyBaby Don't Hurt Mespotify:artist:1Cs0zKBU1kc0i8ypK3B9ai, spotify:artist:1zNqDE7qDGCsyzJwohVaoX, spotify:artist:6AMd49uBDJfhf30Ak2QR5sDavid Guetta, Anne-Marie, Coi Leray2023-04-06https://i.scdn.co/image/ab67616d0000b2730b4ef75c3728599aa4104f7a11140017https://p.scdn.co/mp3-preview/a8f2e176e17e0f6298b42ef8e96118318fdd2b89?cid=9950ac751e34487dbbe027c4fd7f8e99False94UKWLG2300016spotify:user:bradnumber12023-07-11T05:37:45Zbig room,dance pop,edm,pop,pop dance,pop,new jersey underground rap,trap queen0.6020.9107.0-3.4041.00.03080.0012600.0001740.12000.228127.9444.0NaNParlophone UKC Under license to Warner Music UK Limited, © 2023 What A DJ Ltd, P Under license to Warner Music UK Limited, ℗ 2023 What A DJ Ltd
9993spotify:track:6PUzxtIHkv346yP89NzP9XKernkraft 400spotify:artist:7vFpNLbCXbBFs4kFBUlkSlZombie Nationspotify:album:2qmrRoUZQemrKFr9PBMDHdKernkraft 400 Single Mixesspotify:artist:7vFpNLbCXbBFs4kFBUlkSlZombie Nation2006-03-07https://i.scdn.co/image/ab67616d0000b273916e34ccc44c2b56cdd0d7e411285173https://p.scdn.co/mp3-preview/4c12378c6faf04d4d75a0dee5749c8141e79f1f4?cid=9950ac751e34487dbbe027c4fd7f8e99False57DE-Z20-06-00038spotify:user:bradnumber12023-07-11T10:57:16Zgerman techno0.7980.4308.0-7.8390.00.08680.0055000.9010000.14600.487140.0644.0NaNUKW RecordsC 2006 Copyright Control, P 2006 Copyright Control
9994spotify:track:3kcKlOkQQEPVwxwljbGJ5pKernkraft 400 (A Better Day)spotify:artist:0u6GtibW46tFX7koQ6uNJZ, spotify:artist:5Wg2b4Mp42gicxEeDNawf7Topic, A7Sspotify:album:2NIChqkijGw4r4Dqfmg0A3Kernkraft 400 (A Better Day)spotify:artist:0u6GtibW46tFX7koQ6uNJZ, spotify:artist:5Wg2b4Mp42gicxEeDNawf7Topic, A7S2022-06-17https://i.scdn.co/image/ab67616d0000b273e1cafe604179a9438dee7a9411165800https://p.scdn.co/mp3-preview/c65bf1e69065314a08d43e124abd144c21aed3eb?cid=9950ac751e34487dbbe027c4fd7f8e99False79DECE72201091spotify:user:bradnumber12023-07-11T10:57:25Zgerman dance,pop dance,pop edm,uk dance,pop dance,scandipop,uk dance0.6230.72711.0-5.5700.00.05620.1840000.0000200.30900.400125.9754.0NaNVirginC © 2022 Topic, under exclusive license to Universal Music GmbH, P ℗ 2022 Topic, under exclusive license to Universal Music GmbH
9995spotify:track:5k9QrzJFDAp5cXVdzAi02fNever Say Never - Radio Editspotify:artist:1ScZSjoYAihNNm9qlhzDnLVandalismspotify:album:2n506u3HKN3CaEDvAjv5CtNever Say Neverspotify:artist:1ScZSjoYAihNNm9qlhzDnLVandalism2005-10-24https://i.scdn.co/image/ab67616d0000b273b65ad4748f43ba857202aeaf11176640https://p.scdn.co/mp3-preview/e02605a617a8e689068e7ecc695941e572575af7?cid=9950ac751e34487dbbe027c4fd7f8e99False17AUVC00503711spotify:user:bradnumber12023-07-16T09:38:19Zaustralian dance,melbourne bounce0.7200.8419.0-6.3731.00.03400.0003540.0112000.33800.767130.9784.0NaNViciousC 2005 Vicious, a division of Vicious Recordings Pty Ltd, P 2005 Vicious, a division of Vicious Recordings Pty Ltd
9996spotify:track:5ydeCNaWDmFbu4zl0roPAHGroovejet (If This Ain't Love) [feat. Sophie Ellis-Bextor]spotify:artist:4bmymFwDu9zLCiTRUmrewb, spotify:artist:2cBh5lVMg222FFuRU7EfDESpiller, Sophie Ellis-Bextorspotify:album:20Q3pGpYiyicF32x5L8ppHGroovejet (If This Ain't Love) [feat. Sophie Ellis-Bextor]spotify:artist:4bmymFwDu9zLCiTRUmrewbSpiller2000-08-14https://i.scdn.co/image/ab67616d0000b27342781a91264b1d60b43b754c11227619https://p.scdn.co/mp3-preview/4240667eea46663f08d8754bc37bd86c06ba4474?cid=9950ac751e34487dbbe027c4fd7f8e99False62GBCPZ0019728spotify:user:bradnumber12023-07-16T09:39:17Zdisco house,vocal house,dance pop,europop,new wave pop0.7190.8069.0-6.8020.00.03890.0001320.0889000.36100.626123.0374.0NaNDefected RecordsC © 2021 Defected Records Limited, P ℗ 2021 Defected Records Limited
9997spotify:track:0zKbDrEXKpnExhGQRe9dxtLay Lowspotify:artist:2o5jDhtHVPhrJdv3cEQ99ZTiëstospotify:album:0EYKSXXTsON8ZA95BuCoXnLay Lowspotify:artist:2o5jDhtHVPhrJdv3cEQ99ZTiësto2023-01-06https://i.scdn.co/image/ab67616d0000b273c8fdaf1b33263d88246ba90a11153442https://p.scdn.co/mp3-preview/d4e0715dc213858f53a104ee498944a0d759b6cb?cid=9950ac751e34487dbbe027c4fd7f8e99False87NLZ542202348spotify:user:bradnumber12023-07-18T22:06:36Zbig room,brostep,dutch edm,edm,house,pop dance,slap house,trance0.5340.8551.0-4.9230.00.18300.0607000.0002630.34600.420122.0604.0NaNMusical FreedomC © 2023 Musical Freedom Label Ltd., P ℗ 2023 Musical Freedom Label Ltd.
9998spotify:track:3iKuIfvoU50eww6EVzNqHoPadam Padamspotify:artist:4RVnAU35WRWra6OZ3CbbMAKylie Minoguespotify:album:0OHc8STurn45gpk3dyIiw5Padam Padamspotify:artist:4RVnAU35WRWra6OZ3CbbMAKylie Minogue2023-05-19https://i.scdn.co/image/ab67616d0000b2730536a87c690530562f30d49311166266https://p.scdn.co/mp3-preview/da6d6574b173df077e03eacb5249fa49d94d4d88?cid=9950ac751e34487dbbe027c4fd7f8e99False69GB5KW2301017spotify:user:bradnumber12023-07-25T11:57:02Zaustralian dance,australian pop,dance pop,eurodance,new wave pop0.7440.6205.0-7.9301.00.24600.2140000.0011600.10300.711128.1034.0NaNLiberator MusicC 2023 Kylie Minogue/Darenote under exclusive license to BMG Rights Management (UK) Limited, P 2023 Kylie Minogue/Darenote under exclusive license to BMG Rights Management (UK) Limited

Duplicate rows

Most frequently occurring

Track URITrack NameArtist URI(s)Artist Name(s)Album URIAlbum NameAlbum Artist URI(s)Album Artist Name(s)Album Release DateAlbum Image URLDisc NumberTrack NumberTrack Duration (ms)Track Preview URLExplicitPopularityISRCAdded ByAdded AtArtist GenresDanceabilityEnergyKeyLoudnessModeSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoTime SignatureLabelCopyrights# duplicates
23spotify:track:4alHo6RGd0D3OUbTPExTHNJust What I Neededspotify:artist:6DCIj8jNaNpBz8e5oKFPtpThe Carsspotify:album:4tJPWT4r4FSKwy784Qs1FqThe Carsspotify:artist:6DCIj8jNaNpBz8e5oKFPtpThe Cars1978-06-06https://i.scdn.co/image/ab67616d0000b27361e11cce99aab86cb1ce253b13225626https://p.scdn.co/mp3-preview/cafb65956f11cc3e26ee45642bddc1ed69146dd8?cid=9950ac751e34487dbbe027c4fd7f8e99False78USEE17500009spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,classic rock,hard rock,mellow gold,new romantic,new wave,new wave pop,permanent wave,power pop,rock,singer-songwriter,soft rock,synthpop0.6190.5794.0-9.3071.00.04730.01520.0000640.08580.690127.2244.0Elektra RecordsC © 1978 Elektra Records for the United States and WEA International for the world outside of the United States., P ℗ 1978 Elektra Entertainment, a division of Warner Communications, Inc. for the United States and WEA International Inc. for the world outside of the United States.3
42spotify:track:7hQJA50XrCWABAu5v6QZ4iDon't Stop Me Now - Remastered 2011spotify:artist:1dfeR4HaWDbWqFHLkxsg1dQueenspotify:album:21HMAUrbbYSj9NiPPlGumyJazz (Deluxe Remastered Version)spotify:artist:1dfeR4HaWDbWqFHLkxsg1dQueen1978-11-10https://i.scdn.co/image/ab67616d0000b273008b06ec71019afd70153889112209413https://p.scdn.co/mp3-preview/857030fc088d0d4f72f7795b260bb052d20f7146?cid=9950ac751e34487dbbe027c4fd7f8e99False78GBUM71029610spotify:user:bradnumber12021-08-08T09:26:31Zclassic rock,glam rock,rock0.5630.8655.0-5.2771.00.16000.04720.0001910.77000.601156.2714.0Hollywood RecordsC © 2011 Hollywood Records, Inc., P ℗ 2011 Hollywood Records, Inc.3
0spotify:track:0PGwM5vdr5fMejx0IIAYXjI Want You Backspotify:artist:2iE18Oxc8YSumAU232n4rWThe Jackson 5spotify:album:2oJRp9GV4zpFzpnneGZqZH20th Century Masters: The Millennium Collection: Best Of The Jackson 5spotify:artist:2iE18Oxc8YSumAU232n4rWThe Jackson 51999-01-01https://i.scdn.co/image/ab67616d0000b273ea76a3da8040ff4dd01c4a8611180893NaNFalse0USMO19400306spotify:user:bradnumber12021-08-08T09:26:31Zmotown,soul0.6740.5848.0-8.2041.00.03180.46600.0019500.18700.96098.2934.0MotownC © 1999 Motown Record Company L.P., P This Compilation ℗ 1999 Universal Motown Records, a division of UMG Recordings, Inc.2
1spotify:track:0iyEaciAmtiv8xMkBg97FyPayphonespotify:artist:04gDigrS5kc9YWfZHwBETP, spotify:artist:137W8MRPWKqSmrBGDBFSopMaroon 5, Wiz Khalifaspotify:album:3MLzYyjkFBMPTgsso73O36Payphonespotify:artist:04gDigrS5kc9YWfZHwBETPMaroon 52012-01-01https://i.scdn.co/image/ab67616d0000b27320839238d0f69d548674390511231466NaNTrue0USUM71203347spotify:user:bradnumber12021-08-08T09:26:31Zpop,hip hop,pittsburgh rap,pop rap,rap,southern hip hop,trap0.7450.7564.0-4.7491.00.04290.02100.0000000.35600.495109.9994.0A&M / Octone RecordsC © 2012 A&M/Octone Records, P ℗ 2012 Interscope Records2
2spotify:track:0shGCs5AkhwJIgUb0SSz2BThe Way You Look Tonightspotify:artist:1Mxqyy3pSjf8kZZL4QVxS0Frank Sinatraspotify:album:7gmak9ZGm10y4PtZa9SBQnUltimate Sinatraspotify:artist:1Mxqyy3pSjf8kZZL4QVxS0Frank Sinatra2015-04-21https://i.scdn.co/image/ab67616d0000b273b19cb81319fbfd9ed54baeae115201200https://p.scdn.co/mp3-preview/1bc569b4b613a246a1d466e40dba29e707bfea57?cid=9950ac751e34487dbbe027c4fd7f8e99False57USRH10723024spotify:user:bradnumber12021-08-08T09:26:31Zadult standards,easy listening,lounge0.5890.3695.0-8.6780.00.03210.85500.0000000.35200.529132.9544.0FRANK SINATRA HYBRIDC © 2015 Universal Music Enterprises, P This Compilation ℗ 2015 Universal Music Enterprises2
3spotify:track:11IIIe2IeEKR3IdV4s84NmJungle Lovespotify:artist:6QtGlUje9TIkLrgPZrESukSteve Miller Bandspotify:album:5hLazW5a3Ysgy3dncwGgUnGreatest Hits 1974-78spotify:artist:6QtGlUje9TIkLrgPZrESukSteve Miller Band1978-01-01https://i.scdn.co/image/ab67616d0000b273632b907273dba6a6062fb78012189293https://p.scdn.co/mp3-preview/f5c0a06d2fcf457e2b3fa1098730efbf26b451ae?cid=9950ac751e34487dbbe027c4fd7f8e99False48USCA28700783spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,classic rock,hard rock,heartland rock,mellow gold,rock,singer-songwriter,soft rock0.4810.6895.0-11.6291.00.21400.16700.0015300.73900.782144.8514.0CAPITOL CATALOG MKT (C92)C © 1978 Capitol Records, LLC, P ℗ 1978 Capitol Records, LLC2
4spotify:track:1LeWIs2hP2r5yOQnVuYoI5Ain't No Mountain High Enoughspotify:artist:3koiLjNrgRTNbOwViDipeA, spotify:artist:75jNCko3SnEMI5gwGqrbb8Marvin Gaye, Tammi Terrellspotify:album:67Eq3nfl1km9s5ig76Cc8BUnitedspotify:artist:3koiLjNrgRTNbOwViDipeA, spotify:artist:75jNCko3SnEMI5gwGqrbb8Marvin Gaye, Tammi Terrell1967-08-29https://i.scdn.co/image/ab67616d0000b27396e0b7befe3ba88f5a7d5a3f11151666NaNFalse0USMO16700534spotify:user:bradnumber12021-08-08T09:26:31Zclassic soul,motown,neo soul,northern soul,quiet storm,soul,classic soul,motown,soul,southern soul0.6630.6007.0-10.8701.00.03200.43000.0000000.18400.800129.9914.0Motown (Capitol)C © 1967 Motown Records, a Division of UMG Recordings, Inc., P ℗ 1967 Motown Records, a Division of UMG Recordings, Inc.2
5spotify:track:1MTMedlCphum6mRcd8YzvEYou Give Love A Bad Namespotify:artist:58lV9VcRSjABbAbfWS6skpBon Jovispotify:album:0C8Poy7zwJ1kQh2sldyvHmBon Jovi Greatest Hitsspotify:artist:58lV9VcRSjABbAbfWS6skpBon Jovi2010-01-01https://i.scdn.co/image/ab67616d0000b27366e4150921726f65a2c5110c12223146NaNFalse0NLF059290010spotify:user:bradnumber12021-08-08T09:26:31Zglam metal,rock0.5330.9630.0-2.5280.00.05620.03530.0000010.36800.789122.8124.0Universal/Island Def JamC © 2010 The Island Def Jam Music Group, P ℗ 2010 The Island Def Jam Music Group2
6spotify:track:1NrbnHlR2BFREcyWXHIHipWhen I'm Sixty Four - Remastered 2009spotify:artist:3WrFJ7ztbogyGnTHbHJFl2The Beatlesspotify:album:6QaVfG1pHYl1z15ZxkvVDWSgt. Pepper's Lonely Hearts Club Band (Remastered)spotify:artist:3WrFJ7ztbogyGnTHbHJFl2The Beatles1967-06-01https://i.scdn.co/image/ab67616d0000b27334ef8f7d06cf2fc2146f420a19157666https://p.scdn.co/mp3-preview/50d2ef3eab081ff7f73d41068ae0fe15567bbbee?cid=9950ac751e34487dbbe027c4fd7f8e99False68GBAYE0601515spotify:user:bradnumber12021-08-08T09:26:31Zbeatlesque,british invasion,classic rock,merseybeat,psychedelic rock,rock0.7040.2411.0-13.2581.00.04760.62500.0000280.08680.661140.4114.0EMI CatalogueC © 2015 Apple Corps Ltd, P ℗ 2015 Calderstone Productions Limited (a division of Universal Music Group)2
7spotify:track:1SRkKyJ2JjMZgyDWC30zKvMy Best Friend's Girlspotify:artist:6DCIj8jNaNpBz8e5oKFPtpThe Carsspotify:album:4tJPWT4r4FSKwy784Qs1FqThe Carsspotify:artist:6DCIj8jNaNpBz8e5oKFPtpThe Cars1978-06-06https://i.scdn.co/image/ab67616d0000b27361e11cce99aab86cb1ce253b12223253https://p.scdn.co/mp3-preview/cee9a1c1cfacd5bf4cd231cf118e59ac310f6ecf?cid=9950ac751e34487dbbe027c4fd7f8e99False68USEE10170465spotify:user:bradnumber12021-08-08T09:26:31Zalbum rock,classic rock,hard rock,mellow gold,new romantic,new wave,new wave pop,permanent wave,power pop,rock,singer-songwriter,soft rock,synthpop0.7990.6085.0-8.1931.00.04110.08110.0137000.10200.963121.9154.0Elektra RecordsC © 1978 Elektra Records for the United States and WEA International for the world outside of the United States., P ℗ 1978 Elektra Entertainment, a division of Warner Communications, Inc. for the United States and WEA International Inc. for the world outside of the United States.2